Search results for: reverse logistic
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1357

Search results for: reverse logistic

1207 Heart Ailment Prediction Using Machine Learning Methods

Authors: Abhigyan Hedau, Priya Shelke, Riddhi Mirajkar, Shreyash Chaple, Mrunali Gadekar, Himanshu Akula

Abstract:

The heart is the coordinating centre of the major endocrine glandular structure of the body, which produces hormones that profoundly affect the operations of the body, and diagnosing cardiovascular disease is a difficult but critical task. By extracting knowledge and information about the disease from patient data, data mining is a more practical technique to help doctors detect disorders. We use a variety of machine learning methods here, including logistic regression and support vector classifiers (SVC), K-nearest neighbours Classifiers (KNN), Decision Tree Classifiers, Random Forest classifiers and Gradient Boosting classifiers. These algorithms are applied to patient data containing 13 different factors to build a system that predicts heart disease in less time with more accuracy.

Keywords: logistic regression, support vector classifier, k-nearest neighbour, decision tree, random forest and gradient boosting

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1206 Exploiting SLMail Server with a Developed Buffer Overflow with Kali Linux

Authors: Senesh Wijayarathne

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This study focuses on how someone could develop a Buffer Overflow and could use that to exploit the SLMail Server. This study uses a Kali Linux V2018.4 Virtual Machine and Windows 7 - Internet Explorer V8 Virtual Machine (IPv4 Address - 192.168.56.107). This study starts by sending continued bytes to the SLMail Server to find the crashing point range and creating a unique pattern of the length of the crashing point range to control the Extended Instruction Pointer (EIP). Then by sending all characters to SLMail Server, we could observe and find which characters are not rendered properly by the software, also known as Bad Characters. By finding the ‘Jump to the ESP register (JMP ESP) and with the help of ‘Mona Modules’, we could use msfvenom to create a non-stage windows reverse shell payload. By including all the details gathered previously on one script, we could get a system-level reverse shell of the Windows 7 PC. The end of this paper will discuss how to mitigate this vulnerability.

Keywords: slmail server, extended instruction pointer, jump to the esp register, bad characters, virtual machine, windows 7, kali Linux, buffer overflow, Seattle lab, vulnerability

Procedia PDF Downloads 125
1205 Augmenting Cultural Heritage Through 4.0 Technologies: A Research on the Archival Jewelry of the Gianfranco Ferré Research Center

Authors: Greta Rizzi, Ashley Gallitto, Federica Vacca

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Looking at design artifacts as bearers and disseminators of material knowledge and intangible socio-cultural meanings, the significance of archival jewelry was investigated following digital cultural heritage research streams. The application of the reverse engineering concept guided the research path: starting with the study of Gianfranco Ferré's archival jewelry and analyzing its technical heritage and symbolic value, the digitalization, dematerialization, and rematerialization of the artifact were carried out. According to that, the proposed paper results from research conducted within the residency program between the Gianfranco Ferré Research Center (GFRC) and Massachusetts Institute of Technology (MIT), involving both the Design and Mechanical Engineering Departments of Politecnico di Milano. The paper will discuss the analysis of traditional design manufacturing techniques, re-imagined through 3D scanning, 3D modeling, and 3D printing technical knowledge while emphasizing the significance of the designer's role as an explorer of socio-cultural meanings and technological mediators in the analog-digital-analog transition.

Keywords: Archival jewelry, cultural heritage, rematerialization, reverse engineering.

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1204 Negative RT-PCR in a Newborn Infected with Zika Virus: A Case Report

Authors: Vallejo Michael, Acuña Edgar, Roa Juan David, Peñuela Rosa, Parra Alejandra, Casallas Daniela, Rodriguez Sheyla

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Congenital Zika Virus Syndrome is an entity composed by a variety of birth defects presented in newborns that have been exposed to the Zika Virus during pregnancy. The syndrome characteristic features are severe microcephaly, cerebral tissue abnormalities, ophthalmological abnormalities such as uveitis and chorioretinitis, arthrogryposis, clubfoot deformity and muscular tone abnormalities. The confirmatory test is the Reverse transcription polymerase chain reaction (RT-PCR) associated to the physical findings. Here we present the case of a newborn with microcephaly whose mother presented a confirmed Zika Virus infection during the third trimester of pregnancy, despite of the evident findings and the history of Zika infection the RT-PCR in amniotic and cerebrospinal fluid of the newborn was negative. RT-PCR has demonstrated a low sensibility in samples with low viral loads, reason why, we propose a clinical diagnosis in patients with clinical history of Zika Virus infection during pregnancy accompanied by evident clinical manifestations of the child.

Keywords: congenital, Zika virus, microcephaly, reverse transcriptase polymerase chain reaction

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1203 Prediction of Coronary Artery Stenosis Severity Based on Machine Learning Algorithms

Authors: Yu-Jia Jian, Emily Chia-Yu Su, Hui-Ling Hsu, Jian-Jhih Chen

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Coronary artery is the major supplier of myocardial blood flow. When fat and cholesterol are deposit in the coronary arterial wall, narrowing and stenosis of the artery occurs, which may lead to myocardial ischemia and eventually infarction. According to the World Health Organization (WHO), estimated 740 million people have died of coronary heart disease in 2015. According to Statistics from Ministry of Health and Welfare in Taiwan, heart disease (except for hypertensive diseases) ranked the second among the top 10 causes of death from 2013 to 2016, and it still shows a growing trend. According to American Heart Association (AHA), the risk factors for coronary heart disease including: age (> 65 years), sex (men to women with 2:1 ratio), obesity, diabetes, hypertension, hyperlipidemia, smoking, family history, lack of exercise and more. We have collected a dataset of 421 patients from a hospital located in northern Taiwan who received coronary computed tomography (CT) angiography. There were 300 males (71.26%) and 121 females (28.74%), with age ranging from 24 to 92 years, and a mean age of 56.3 years. Prior to coronary CT angiography, basic data of the patients, including age, gender, obesity index (BMI), diastolic blood pressure, systolic blood pressure, diabetes, hypertension, hyperlipidemia, smoking, family history of coronary heart disease and exercise habits, were collected and used as input variables. The output variable of the prediction module is the degree of coronary artery stenosis. The output variable of the prediction module is the narrow constriction of the coronary artery. In this study, the dataset was randomly divided into 80% as training set and 20% as test set. Four machine learning algorithms, including logistic regression, stepwise regression, neural network and decision tree, were incorporated to generate prediction results. We used area under curve (AUC) / accuracy (Acc.) to compare the four models, the best model is neural network, followed by stepwise logistic regression, decision tree, and logistic regression, with 0.68 / 79 %, 0.68 / 74%, 0.65 / 78%, and 0.65 / 74%, respectively. Sensitivity of neural network was 27.3%, specificity was 90.8%, stepwise Logistic regression sensitivity was 18.2%, specificity was 92.3%, decision tree sensitivity was 13.6%, specificity was 100%, logistic regression sensitivity was 27.3%, specificity 89.2%. From the result of this study, we hope to improve the accuracy by improving the module parameters or other methods in the future and we hope to solve the problem of low sensitivity by adjusting the imbalanced proportion of positive and negative data.

Keywords: decision support, computed tomography, coronary artery, machine learning

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1202 An Assessment of Self-Perceived Health after the Death of a Spouse among the Elderly

Authors: Shu-Hsi Ho

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The problems of aging and number of widowed peers gradually rise in Taiwan. It is worth to concern the related issues for elderly after the death of a spouse. Hence, this study is to examine the impact of spousal death on the surviving spouse’s self-perceived health and mental health for the elderly in Taiwan. A cross section data design and ordered logistic regression models are applied to investigate whether marriage is associated significantly to self-perceived health and mental health for the widowed older Taiwanese. The results indicate that widowed marriage shows significant negative effects on self-perceived health and mental health regardless of widows or widowers. Among them, widows might be more likely to show worse mental health than widowers. The belief confirms that marriage provides effective sources to promote self-perceived health and mental health, particularly for females. In addition, since the social welfare system is not perfect in Taiwan, the findings also suggest that family and social support reveal strongly association with the self-perceived health and mental health for the widows and widowers elderly.

Keywords: logistic regression models, self-perceived health, widow, widower

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1201 Monitoring and Evaluation of the Reverse Osmosis Reject Wastewater from the Sulaibiya Wastewater Treatment Plant in Kuwait

Authors: Mishari Khajah, Mohd. Elmuntasir Ahmed, Abdullah Al-Matouq, Farah Al-Ajeel, Fatemah Dashti, Ahmed Shishter

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The overall aim of this study was to monitor and evaluate the effluent quality of a reverse osmosis (RO) reject wastewater from the biggest wastewater treatment plant in the world that is using RO and ultrafiltration membranes in their processes to reclaim water for indirect potable water reuse from municipal wastewaters. The RO reject wastewater or brine included various contaminants that could harm the human health and the environment such as trace organics, organic matters, heavy metals, nutrients and pathogens. Unfortunately, there are no legally binding regulatory guidelines for brine management in Kuwait as many countries around the world. This study monitors and evaluate the RO reject wastewater (brine) generated from the Sulaibiya Wastewater Treatment Plant. Samples were collected and analyzed about 37 parameters for one-year period, twice a month, and compare it to Kuwait Environment Public Authority, KEPA. Results showed that the heavy metals parameters were above KEPA standards, which needs to be treated.

Keywords: domestic wastewater, management, potable water, RO reject wastewater, Sulaibiya wastewater treatment plant

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1200 Identifying Artifacts in SEM-EDS of Fouled RO Membranes Used for the Treatment of Brackish Groundwater Through Raman and ICP-MS Analysis

Authors: Abhishek Soti, Aditya Sharma, Akhilendra Bhushan Gupta

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Fouled reverse osmosis membranes are primarily characterized by Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectrometer (EDS) for a detailed investigation of foulants; however, this has severe limitations on several accounts. Apart from inaccuracy in spectral properties and inevitable interferences and interactions between sample and instrument, misidentification of elements due to overlapping peaks is a significant drawback of EDS. This paper discusses this limitation by analyzing fouled polyamide RO membranes derived from community RO plants of Rajasthan treating brackish water via a combination of results obtained from EDS and Raman spectroscopy and cross corroborating with ICP-MS analysis of water samples prepared by dissolving the deposited salts. The anomalous behavior of different morphic forms of CaCO₃ in aqueous suspensions tends to introduce false reporting of the presence of certain heavy metals and rare earth metals in the scales of the fouled RO membranes used for treating brackish groundwater when analyzed using the commonly adopted techniques like SEM-EDS or Raman spectrometry. Peaks of CaCO₃ reflected in EDS spectra of the membrane were found to be misinterpreted as Scandium due to the automatic assignment of elements by the software. Similarly, the morphic forms merged with the dominant peak of CaCO₃ might be reflected as a single peak of Molybdenum in the Raman spectrum. A subsequent ICP-MS analysis of the deposited salts showed that both Sc and Mo were below detectable levels. It is always essential to cross-confirm the results through a destructive analysis method to avoid such interferences. It is further recommended to study different morphic forms of CaCO₃ scales, as they exhibit anomalous properties like reverse solubility with temperature and hence altered precipitation tendencies, for an accurate description of the composition of scales, which is vital for the smooth functioning of RO systems.

Keywords: reverse osmosis, foulant analysis, groundwater, EDS, artifacts

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1199 Taguchi Method for Analyzing a Flexible Integrated Logistics Network

Authors: E. Behmanesh, J. Pannek

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Logistics network design is known as one of the strategic decision problems. As these kinds of problems belong to the category of NP-hard problems, traditional ways are failed to find an optimal solution in short time. In this study, we attempt to involve reverse flow through an integrated design of forward/reverse supply chain network that formulated into a mixed integer linear programming. This Integrated, multi-stages model is enriched by three different delivery path which makes the problem more complex. To tackle with such an NP-hard problem a revised random path direct encoding method based memetic algorithm is considered as the solution methodology. Each algorithm has some parameters that need to be investigate to reveal the best performance. In this regard, Taguchi method is adapted to identify the optimum operating condition of the proposed memetic algorithm to improve the results. In this study, four factors namely, population size, crossover rate, local search iteration and a number of iteration are considered. Analyzing the parameters and improvement in results are the outlook of this research.

Keywords: integrated logistics network, flexible path, memetic algorithm, Taguchi method

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1198 Fabrication of High-Power AlGaN/GaN Schottky Barrier Diode with Field Plate Design

Authors: Chia-Jui Yu, Chien-Ju Chen, Jyun-Hao Liao, Chia-Ching Wu, Meng-Chyi Wu

Abstract:

In this letter, we demonstrate high-performance AlGaN/GaN planar Schottky barrier diodes (SBDs) on the silicon substrate with field plate structure for increasing breakdown voltage VB. A low turn-on resistance RON (3.55 mΩ-cm2), low reverse leakage current (< 0.1 µA) at -100 V, and high reverse breakdown voltage VB (> 1.1 kV) SBD has been fabricated. A virgin SBD exhibited a breakdown voltage (measured at 1 mA/mm) of 615 V, and with the field plate technology device exhibited a breakdown voltage (measured at 1 mA/mm) of 1525 V (the anode–cathode distance was LAC = 40 µm). Devices without the field plate design exhibit a Baliga’s figure of merit of VB2/ RON = 60.2 MW/cm2, whereas devices with the field plate design show a Baliga’s figure of merit of VB2/ RON = 340.9 MW/cm2 (the anode–cathode distance was LAC = 20 µm).

Keywords: AlGaN/GaN heterostructure, silicon substrate, Schottky barrier diode (SBD), high breakdown voltage, Baliga’s figure-of-merit, field plate

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1197 Assessment of Pastoralist-Crop Farmers Conflict and Food Security of Farming Households in Kwara State, Nigeria

Authors: S. A. Salau, I. F. Ayanda, I. Afe, M. O. Adesina, N. B. Nofiu

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Food insecurity is still a critical challenge among rural and urban households in Nigeria. The country’s food insecurity situation became more pronounced due to frequent conflict between pastoralist and crop farmers. Thus, this study assesses pastoralist-crop farmers’ conflict and food security of farming households in Kwara state, Nigeria. The specific objectives are to measure the food security status of the respondents, quantify pastoralist- crop farmers’ conflict, determine the effect of pastoralist- crop farmers conflict on food security and describe the effective coping strategies adopted by the respondents to reduce the effect of food insecurity. A combination of purposive and simple random sampling techniques will be used to select 250 farming households for the study. The analytical tools include descriptive statistics, Likert-scale, logistic regression, and food security index. Using the food security index approach, the percentage of households that were food secure and insecure will be known. Pastoralist- crop farmers’ conflict will be measured empirically by quantifying loses due to the conflict. The logistic regression will indicate if pastoralist- crop farmers’ conflict is a critical determinant of food security among farming households in the study area. The coping strategies employed by the respondents in cushioning the effects of food insecurity will also be revealed. Empirical studies on the effect of pastoralist- crop farmers’ conflict on food security are rare in the literature. This study will quantify conflict and reveal the direction as well as the extent of the relationship between conflict and food security. It could contribute to the identification and formulation of strategies for the minimization of conflict among pastoralist and crop farmers in an attempt to reduce food insecurity. Moreover, this study could serve as valuable reference material for future researches and open up new areas for further researches.

Keywords: agriculture, conflict, coping strategies, food security, logistic regression

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1196 Developing an Advanced Algorithm Capable of Classifying News, Articles and Other Textual Documents Using Text Mining Techniques

Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial Neural network, Competitive dynamics, Logistic Regression, Text classification, Text mining

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1195 Nuclear Fuel Safety Threshold Determined by Logistic Regression Plus Uncertainty

Authors: D. S. Gomes, A. T. Silva

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Analysis of the uncertainty quantification related to nuclear safety margins applied to the nuclear reactor is an important concept to prevent future radioactive accidents. The nuclear fuel performance code may involve the tolerance level determined by traditional deterministic models producing acceptable results at burn cycles under 62 GWd/MTU. The behavior of nuclear fuel can simulate applying a series of material properties under irradiation and physics models to calculate the safety limits. In this study, theoretical predictions of nuclear fuel failure under transient conditions investigate extended radiation cycles at 75 GWd/MTU, considering the behavior of fuel rods in light-water reactors under reactivity accident conditions. The fuel pellet can melt due to the quick increase of reactivity during a transient. Large power excursions in the reactor are the subject of interest bringing to a treatment that is known as the Fuchs-Hansen model. The point kinetic neutron equations show similar characteristics of non-linear differential equations. In this investigation, the multivariate logistic regression is employed to a probabilistic forecast of fuel failure. A comparison of computational simulation and experimental results was acceptable. The experiments carried out use the pre-irradiated fuels rods subjected to a rapid energy pulse which exhibits the same behavior during a nuclear accident. The propagation of uncertainty utilizes the Wilk's formulation. The variables chosen as essential to failure prediction were the fuel burnup, the applied peak power, the pulse width, the oxidation layer thickness, and the cladding type.

Keywords: logistic regression, reactivity-initiated accident, safety margins, uncertainty propagation

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1194 Reverse Osmosis Application on Sewage Tertiary Treatment

Authors: Elisa K. Schoenell, Cristiano De Oliveira, Luiz R. H. Dos Santos, Alexandre Giacobbo, Andréa M. Bernardes, Marco A. S. Rodrigues

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Water is an indispensable natural resource, which must be preserved to human activities as well the ecosystems. However, the sewage discharge has been contaminating water resources. Conventional treatment, such as physicochemical treatment followed by biological processes, has not been efficient to the complete degradation of persistent organic compounds, such as medicines and hormones. Therefore, the use of advanced technologies to sewage treatment has become urgent and necessary. The aim of this study was to apply Reverse Osmosis (RO) on sewage tertiary treatment from a Waste Water Treatment Plant (WWTP) in south Brazil. It was collected 200 L of sewage pre-treated by wetland with aquatic macrophytes. The sewage was treated in a RO pilot plant, using a polyamide membrane BW30-4040 model (DOW FILMTEC), with 7.2 m² membrane area. In order to avoid damage to the equipment, this system contains a pleated polyester filter with 5 µm pore size. It was applied 8 bar until achieve 5 times of concentration, obtaining 80% of recovery of permeate, with 10 L.min-1 of concentrate flow rate. Samples of sewage pre-treated on WWTP, permeate and concentrate generated on RO was analyzed for physicochemical parameters and by gas chromatography (GC) to qualitative analysis of organic compounds. The results proved that the sewage treated on WWTP does not comply with the limit of phosphorus and nitrogen of Brazilian legislation. Besides this, it was found many organic compounds in this sewage, such as benzene, which is carcinogenic. Analyzing permeate results, it was verified that the RO as sewage tertiary treatment was efficient to remove of physicochemical parameters, achieving 100% of iron, copper, zinc and phosphorus removal, 98% of color removal, 91% of BOD and 62% of ammoniacal nitrogen. RO was capable of removing organic compounds, however, it was verified the presence of some organic compounds on de RO permeate, showing that RO did not have the capacity of removal all organic compounds of sewage. It has to be considered that permeate showed lower intensity of peaks in chromatogram in comparison to the sewage of WWTP. It is important to note that the concentrate generate on RO needs a treatment before its disposal in environment.

Keywords: organic compounds, reverse osmosis, sewage treatment, tertiary treatment

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1193 Modeling and Analysis Of Occupant Behavior On Heating And Air Conditioning Systems In A Higher Education And Vocational Training Building In A Mediterranean Climate

Authors: Abderrahmane Soufi

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The building sector is the largest consumer of energy in France, accounting for 44% of French consumption. To reduce energy consumption and improve energy efficiency, France implemented an energy transition law targeting 40% energy savings by 2030 in the tertiary building sector. Building simulation tools are used to predict the energy performance of buildings but the reliability of these tools is hampered by discrepancies between the real and simulated energy performance of a building. This performance gap lies in the simplified assumptions of certain factors, such as the behavior of occupants on air conditioning and heating, which is considered deterministic when setting a fixed operating schedule and a fixed interior comfort temperature. However, the behavior of occupants on air conditioning and heating is stochastic, diverse, and complex because it can be affected by many factors. Probabilistic models are an alternative to deterministic models. These models are usually derived from statistical data and express occupant behavior by assuming a probabilistic relationship to one or more variables. In the literature, logistic regression has been used to model the behavior of occupants with regard to heating and air conditioning systems by considering univariate logistic models in residential buildings; however, few studies have developed multivariate models for higher education and vocational training buildings in a Mediterranean climate. Therefore, in this study, occupant behavior on heating and air conditioning systems was modeled using logistic regression. Occupant behavior related to the turn-on heating and air conditioning systems was studied through experimental measurements collected over a period of one year (June 2023–June 2024) in three classrooms occupied by several groups of students in engineering schools and professional training. Instrumentation was provided to collect indoor temperature and indoor relative humidity in 10-min intervals. Furthermore, the state of the heating/air conditioning system (off or on) and the set point were determined. The outdoor air temperature, relative humidity, and wind speed were collected as weather data. The number of occupants, age, and sex were also considered. Logistic regression was used for modeling an occupant turning on the heating and air conditioning systems. The results yielded a proposed model that can be used in building simulation tools to predict the energy performance of teaching buildings. Based on the first months (summer and early autumn) of the investigations, the results illustrate that the occupant behavior of the air conditioning systems is affected by the indoor relative humidity and temperature in June, July, and August and by the indoor relative humidity, temperature, and number of occupants in September and October. Occupant behavior was analyzed monthly, and univariate and multivariate models were developed.

Keywords: occupant behavior, logistic regression, behavior model, mediterranean climate, air conditioning, heating

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1192 Modeling of the Effect of Explosives, Geological and Geotechnical Parameters on the Stability of Rock Masses Case of Marrakech: Agadir Highway, Morocco

Authors: Taoufik Benchelha, Toufik Remmal, Rachid El Hamdouni, Hamou Mansouri, Houssein Ejjaouani, Halima Jounaid, Said Benchelha

Abstract:

During the earthworks for the construction of Marrakech-Agadir highway in southern Morocco, which crosses mountainous areas of the High Western Atlas, the main problem faced is the stability of the slopes. Indeed, the use of explosives as a means of excavation associated with the geological structure of the terrain encountered can trigger major ruptures and cause damage which depends on the intrinsic characteristics of the rock mass. The study consists of a geological and geotechnical analysis of several unstable zones located along the route, mobilizing millions of cubic meters of rock, with deduction of the parameters influencing slope stability. From this analysis, a predictive model for rock mass stability is carried out, based on a statistic method of logistic regression, in order to predict the geomechanical behavior of the rock slopes constrained by earthworks.

Keywords: explosive, logistic regression, rock mass, slope stability

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1191 Logistic and Its Importance in Turkish Food Sector and an Analysis of the Logistics Sector in Turkey

Authors: Şule Turhan, Özlem Turan

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Permanence in the international markets for many global companies is about being known as having effective logistics which targets customer satisfaction management and lower costs. Under competitive conditions, the necessity of providing the products to customers quickly and on time for the companies which constantly aim to improve their profitability increased the strategic importance of the logistics concept. Food logistic is one of the most difficult areas in logistics. In the process from manufacturer to final consumer, quality and hygiene standards must be provided constantly. In food logistics, reliable and extensive service network has great importance and on time delivery is the target. Developing logistics industry provide the supply of foods in the country and the development of export markets more quickly and has an important role in providing added value to the country's economy. Turkey that creates a bridge between the east and the west is an attractive market for logistics companies. In this study, by examining both the place and the importance of logistics in Turkish food sector, recommendations will be made for the food industry.

Keywords: logistics, Turkish food industry, competition, food industry

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1190 Examining Bulling Rates among Youth with Intellectual Disabilities

Authors: Kaycee L. Bills

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Adolescents and youth who are members of a minority group are more likely to experience higher rates of bullying in comparison to other student demographics. Specifically, adolescents with intellectual disabilities are a minority population that is more susceptible to experience unfair treatment in social settings. This study employs the 2015 Wave of the National Crime Victimization Survey – School Crime Supplement (NCVS/SCS) longitudinal dataset to explore bullying rates experienced among adolescents with intellectual disabilities. This study uses chi-square testing and a logistic regression to analyze if having a disability influences the likelihood of being bullied in comparison to other student demographics. Results of the chi-square testing and the logistic regression indicate that adolescent students who were identified as having a disability were approximately four times more likely to experience higher bullying rates in comparison to all other majority and minority student populations. Thus, it means having a disability resulted in higher bullying rates in comparison to all student groups.

Keywords: disability, bullying, social work, school bullying

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1189 Eradication of Apple mosaic virus from Corylus avellana L. via Cryotherapy and Confirmation of Virus-Free Plants via Reverse Transcriptase Polymerase Chain Reaction

Authors: Ergun Kaya

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Apple mosaic virus (ApMV) is an ilarvirus causing harmful damages and product loses in many plant species. Because of xylem and phloem vessels absence, plant meristem tissues used for meristem cultures are virus-free, but sometimes only meristem cultures are not sufficient for virus elimination. Cryotherapy, a new method based on cryogenic techniques, is used for virus elimination. In this technique, 0.1-0.3mm meristems are excised from organized shoot apex of a selected in vitro donor plant and these meristems are frozen in liquid nitrogen (-196 °C) using suitable cryogenic technique. The aim of this work was to develop an efficient procedure for ApMV-free hazelnut via cryotherapy technique and confirmation of virus-free plants using Reverse Transcriptase-PCR technique. 100% virus free plantlets were obtained using droplet-vitrification method involved cold hardening in vitro cultures of hazelnut, 24 hours sucrose preculture of meristems on MS medium supplemented with 0.4M sucrose, and a 90 min PVS2 treatment in droplets.

Keywords: droplet vitrification, hazelnut, liquid nitrogen, PVS2

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1188 Gender Estimation by Means of Quantitative Measurements of Foramen Magnum: An Analysis of CT Head Images

Authors: Thilini Hathurusinghe, Uthpalie Siriwardhana, W. M. Ediri Arachchi, Ranga Thudugala, Indeewari Herath, Gayani Senanayake

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The foramen magnum is more prone to protect than other skeletal remains during high impact and severe disruptive injuries. Therefore, it is worthwhile to explore whether these measurements can be used to determine the human gender which is vital in forensic and anthropological studies. The idea was to find out the ability to use quantitative measurements of foramen magnum as an anatomical indicator for human gender estimation and to evaluate the gender-dependent variations of foramen magnum using quantitative measurements. Randomly selected 113 subjects who underwent CT head scans at Sri Jayawardhanapura General Hospital of Sri Lanka within a period of six months, were included in the study. The sample contained 58 males (48.76 ± 14.7 years old) and 55 females (47.04 ±15.9 years old). Maximum length of the foramen magnum (LFM), maximum width of the foramen magnum (WFM), minimum distance between occipital condyles (MnD) and maximum interior distance between occipital condyles (MxID) were measured. Further, AreaT and AreaR were also calculated. The gender was estimated using binomial logistic regression. The mean values of all explanatory variables (LFM, WFM, MnD, MxID, AreaT, and AreaR) were greater among male than female. All explanatory variables except MnD (p=0.669) were statistically significant (p < 0.05). Significant bivariate correlations were demonstrated by AreaT and AreaR with the explanatory variables. The results evidenced that WFM and MxID were the best measurements in predicting gender according to binomial logistic regression. The estimated model was: log (p/1-p) =10.391-0.136×MxID-0.231×WFM, where p is the probability of being a female. The classification accuracy given by the above model was 65.5%. The quantitative measurements of foramen magnum can be used as a reliable anatomical marker for human gender estimation in the Sri Lankan context.

Keywords: foramen magnum, forensic and anthropological studies, gender estimation, logistic regression

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1187 Adapting an Accurate Reverse-time Migration Method to USCT Imaging

Authors: Brayden Mi

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Reverse time migration has been widely used in the Petroleum exploration industry to reveal subsurface images and to detect rock and fluid properties since the early 1980s. The seismic technology involves the construction of a velocity model through interpretive model construction, seismic tomography, or full waveform inversion, and the application of the reverse-time propagation of acquired seismic data and the original wavelet used in the acquisition. The methodology has matured from 2D, simple media to present-day to handle full 3D imaging challenges in extremely complex geological conditions. Conventional Ultrasound computed tomography (USCT) utilize travel-time-inversion to reconstruct the velocity structure of an organ. With the velocity structure, USCT data can be migrated with the “bend-ray” method, also known as migration. Its seismic application counterpart is called Kirchhoff depth migration, in which the source of reflective energy is traced by ray-tracing and summed to produce a subsurface image. It is well known that ray-tracing-based migration has severe limitations in strongly heterogeneous media and irregular acquisition geometries. Reverse time migration (RTM), on the other hand, fully accounts for the wave phenomena, including multiple arrives and turning rays due to complex velocity structure. It has the capability to fully reconstruct the image detectable in its acquisition aperture. The RTM algorithms typically require a rather accurate velocity model and demand high computing powers, and may not be applicable to real-time imaging as normally required in day-to-day medical operations. However, with the improvement of computing technology, such a computational bottleneck may not present a challenge in the near future. The present-day (RTM) algorithms are typically implemented from a flat datum for the seismic industry. It can be modified to accommodate any acquisition geometry and aperture, as long as sufficient illumination is provided. Such flexibility of RTM can be conveniently implemented for the application in USCT imaging if the spatial coordinates of the transmitters and receivers are known and enough data is collected to provide full illumination. This paper proposes an implementation of a full 3D RTM algorithm for USCT imaging to produce an accurate 3D acoustic image based on the Phase-shift-plus-interpolation (PSPI) method for wavefield extrapolation. In this method, each acquired data set (shot) is propagated back in time, and a known ultrasound wavelet is propagated forward in time, with PSPI wavefield extrapolation and a piece-wise constant velocity model of the organ (breast). The imaging condition is then applied to produce a partial image. Although each image is subject to the limitation of its own illumination aperture, the stack of multiple partial images will produce a full image of the organ, with a much-reduced noise level if compared with individual partial images.

Keywords: illumination, reverse time migration (RTM), ultrasound computed tomography (USCT), wavefield extrapolation

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1186 Food Insecurity Assessment, Consumption Pattern and Implications of Integrated Food Security Phase Classification: Evidence from Sudan

Authors: Ahmed A. A. Fadol, Guangji Tong, Wlaa Mohamed

Abstract:

This paper provides a comprehensive analysis of food insecurity in Sudan, focusing on consumption patterns and their implications, employing the Integrated Food Security Phase Classification (IPC) assessment framework. Years of conflict and economic instability have driven large segments of the population in Sudan into crisis levels of acute food insecurity according to the (IPC). A substantial number of people are estimated to currently face emergency conditions, with an additional sizeable portion categorized under less severe but still extreme hunger levels. In this study, we explore the multifaceted nature of food insecurity in Sudan, considering its historical, political, economic, and social dimensions. An analysis of consumption patterns and trends was conducted, taking into account cultural influences, dietary shifts, and demographic changes. Furthermore, we employ logistic regression and random forest analysis to identify significant independent variables influencing food security status in Sudan. Random forest clearly outperforms logistic regression in terms of area under curve (AUC), accuracy, precision and recall. Forward projections of the IPC for Sudan estimate that 15 million individuals are anticipated to face Crisis level (IPC Phase 3) or worse acute food insecurity conditions between October 2023 and February 2024. Of this, 60% are concentrated in Greater Darfur, Greater Kordofan, and Khartoum State, with Greater Darfur alone representing 29% of this total. These findings emphasize the urgent need for both short-term humanitarian aid and long-term strategies to address Sudan's deepening food insecurity crisis.

Keywords: food insecurity, consumption patterns, logistic regression, random forest analysis

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1185 Developing Logistics Indices for Turkey as an an Indicator of Economic Activity

Authors: Gizem İntepe, Eti Mizrahi

Abstract:

Investment and financing decisions are influenced by various economic features. Detailed analysis should be conducted in order to make decisions not only by companies but also by governments. Such analysis can be conducted either at the company level or on a sectoral basis to reduce risks and to maximize profits. Sectoral disaggregation caused by seasonality effects, subventions, data advantages or disadvantages may appear in sectors behaving parallel to BIST (Borsa Istanbul stock exchange) Index. Proposed logistic indices could serve market needs as a decision parameter in sectoral basis and also helps forecasting activities in import export volume changes. Also it is an indicator of logistic activity, which is also a sign of economic mobility at the national level. Publicly available data from “Ministry of Transport, Maritime Affairs and Communications” and “Turkish Statistical Institute” is utilized to obtain five logistics indices namely as; exLogistic, imLogistic, fLogistic, dLogistic and cLogistic index. Then, efficiency and reliability of these indices are tested.

Keywords: economic activity, export trade data, import trade data, logistics indices

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1184 The Effect of Patient Positioning on Pleth Variability Index during Surgery

Authors: Omid Azimaraghi, Noushin Khazaei

Abstract:

Background: Fluid therapy is an important aspect of the perioperative period and a major challenge for anesthesiologists. To authors best knowledge, there is a lack of strong guidance and evidence regarding the optimal approach to fluid therapy. Therefore a variety of medical devices have been introduced to help physicians. In this study, we aimed to evaluate the effectiveness of pleth variability index in guiding fluid therapy in different patient positions. Materials and Methods: Inclusion criteria consisted of patients aged 18-50 years old and classified as American Society of Anesthesiologists physical status I and II, who were candidates for elective thyroidectomy surgery. In total, 36 patients meeting the inclusion criteria were enrolled in the study. After induction of anesthesia and start of mechanical ventilation Pleth variability index was measured in the supine position, then patients were placed in Trendelenburg and reverse Trendelenburg position (30 degrees, 5 minutes); Pleth Variability Index has measured again in the mentioned positions. Results: Mean PVI (Pleth Variability Index) in the supine position was 14.3 ± 3.7 in comparison to 21.5 ± 4.3 in the reverse Trendelenburg position. The mean PVI in Trendelenburg position was 9.1 ± 2.0 in Trendelenburg position (p < 0.05). Conclusion: In conclusion, we found that Pleth Variability Index varies with patient position and this should be taken into account when using this index during fluid therapy.

Keywords: fluid therapy, Pleth Variability Index, position, surgery

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1183 Isothermal Solid-Phase Amplification System for Detection of Yersinia pestis

Authors: Olena Mayboroda, Angel Gonzalez Benito, Jonathan Sabate Del Rio, Marketa Svobodova, Sandra Julich, Herbert Tomaso, Ciara K. O'Sullivan, Ioanis Katakis

Abstract:

DNA amplification is required for most molecular diagnostic applications but conventional PCR has disadvantages for field testing. Isothermal amplification techniques are being developed to respond to this problem. One of them is the Recombinase Polymerase Amplification (RPA) that operates at isothermal conditions without sacrificing specificity and sensitivity in easy-to-use formats. In this work RPA was used for the optical detection of solid-phase amplification of the potential biowarfare agent Yersinia pestis. Thiolated forward primers were immobilized on the surface of maleimide-activated microtitre plates for the quantitative detection of synthetic and genomic DNA, with elongation occurring only in the presence of the specific template DNA and solution phase reverse primers. Quantitative detection was achieved via the use of biotinylated reverse primers and post-amplification addition of streptavidin-HRP conjugate. The overall time of amplification and detection was less than 1 hour at a constant temperature of 37oC. Single-stranded and double-stranded DNA sequences were detected achieving detection limits of 4.04*10-13 M and 3.14*10-16 M, respectively. The system demonstrated high specificity with negligible responses to non-specific targets.

Keywords: recombinase polymerase amplification, Yersinia pestis, solid-phase detection, ELONA

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1182 Time's Arrow and Entropy: Violations to the Second Law of Thermodynamics Disrupt Time Perception

Authors: Jason Clarke, Michaela Porubanova, Angela Mazzoli, Gulsah Kut

Abstract:

What accounts for our perception that time inexorably passes in one direction, from the past to the future, the so-called arrow of time, given that the laws of physics permit motion in one temporal direction to also happen in the reverse temporal direction? Modern physics says that the reason for time’s unidirectional physical arrow is the relationship between time and entropy, the degree of disorder in the universe, which is evolving from low entropy (high order; thermal disequilibrium) toward high entropy (high disorder; thermal equilibrium), the second law of thermodynamics. Accordingly, our perception of the direction of time, from past to future, is believed to emanate as a result of the natural evolution of entropy from low to high, with low entropy defining our notion of ‘before’ and high entropy defining our notion of ‘after’. Here we explored this proposed relationship between entropy and the perception of time’s arrow. We predicted that if the brain has some mechanism for detecting entropy, whose output feeds into processes involved in constructing our perception of the direction of time, presentation of violations to the expectation that low entropy defines ‘before’ and high entropy defines ‘after’ would alert this mechanism, leading to measurable behavioral effects, namely a disruption in duration perception. To test this hypothesis, participants were shown briefly-presented (1000 ms or 500 ms) computer-generated visual dynamic events: novel 3D shapes that were seen either to evolve from whole figures into parts (low to high entropy condition) or were seen in the reverse direction: parts that coalesced into whole figures (high to low entropy condition). On each trial, participants were instructed to reproduce the duration of their visual experience of the stimulus by pressing and releasing the space bar. To ensure that attention was being deployed to the stimuli, a secondary task was to report the direction of the visual event (forward or reverse motion). Participants completed 60 trials. As predicted, we found that duration reproduction was significantly longer for the high to low entropy condition compared to the low to high entropy condition (p=.03). This preliminary data suggests the presence of a neural mechanism that detects entropy, which is used by other processes to construct our perception of the direction of time or time’s arrow.

Keywords: time perception, entropy, temporal illusions, duration perception

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1181 Proportion and Factors Associated with Presumptive Tuberculosis among Suspected Pediatric Tuberculosis Patients

Authors: Naima Nur, Safa Islam, Saeema Islam, Md. Faridul Alam

Abstract:

Background: The worldwide increase in pediatric presumptive tuberculosis (TB) is the most life-threatening challenge in effectively controlling TB. The objective of this study was to determine the proportion of presumptive TB and the factors associated with it. Methods: A cross-sectional study was conducted between March and November 2013 at ICDDR-Bangladesh. Two hundred twelve pulmonary and extra-pulmonary specimens were collected from 84 suspected pediatric patients diagnosed with TB based on their clinical symptoms/radiological findings. Presumptive TB and confirmed TB were considered presumptive TB and non-presumptive TB and were isolated by smear-microscopy, culture, and GeneXpert. Logistic regression was used to analyze associations between outcome and predictor variables. Results: The proportion of presumptive TB was 85.7%, and 14.3% of non-presumptive TB. In presumptive TB, vaccine scars, family TB history, and school-going children were 16.6%, 33.3%, and 56.9%, respectively. In contrast, vaccine scars and family TB history were 8.3%, and school-going children were 58.3% in non-presumptive TB. Significant factors did not appear in the logistic regression analysis. Conclusion: Despite the high proportion of presumptive TB, there was no statistically significant between presumptive TB and non-presumptive TB.

Keywords: presumptive tuberculosis, confirmed tuberculosis, patient's characteristics, diagnosis

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1180 Leveraging Business to Business Collaborations to Optimize Reverse Haul Logistics

Authors: Pallav Singh, Rajesh Yabaji, Rajesh Dhir, Chanakya Hridaya

Abstract:

Supply Chain Costs for the Indian Industries have been on an exponential trend due to steep inflation on fundamental cost factors – Fuel, Labour, Rents. In this changing context organizations have been focusing on adopting multiple approaches to keep logistics costs under control to protect the profit margins. The lever of ‘Business to Business (B2B) collaboration’ can be used by organizations to garner higher value. Given the context of Indian Logistics Industry the penetration of B2B Collaboration initiatives have been limited. This paper outlines a structured framework for adoption of B2B collaboration through discussion of a successful initiative between ITC’s Leaf Tobacco Business and a leading Indian Media House. Multiple barriers to such a collaborative process exist which need to be addressed through comprehensive structured approaches. This paper outlines a generic framework approach to B2B collaboration for the Indian Logistics Space, outlining the guidelines for arriving at potential opportunities, identification of collaborators, effective tie-up process, design of operations and sustenance factors. The generic methods outlined can be used in any other industry and also builds a foundation for further research on many topics.

Keywords: business to business collaboration, reverse haul logistics, transportation cost optimization, exports logistics

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1179 An Automated Stock Investment System Using Machine Learning Techniques: An Application in Australia

Authors: Carol Anne Hargreaves

Abstract:

A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.

Keywords: machine learning, stock market trading, logistic regression, cluster analysis, factor analysis, decision trees, neural networks, automated stock investment system

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1178 Minimizing the Impact of Covariate Detection Limit in Logistic Regression

Authors: Shahadut Hossain, Jacek Wesolowski, Zahirul Hoque

Abstract:

In many epidemiological and environmental studies covariate measurements are subject to the detection limit. In most applications, covariate measurements are usually truncated from below which is known as left-truncation. Because the measuring device, which we use to measure the covariate, fails to detect values falling below the certain threshold. In regression analyses, it causes inflated bias and inaccurate mean squared error (MSE) to the estimators. This paper suggests a response-based regression calibration method to correct the deleterious impact introduced by the covariate detection limit in the estimators of the parameters of simple logistic regression model. Compared to the maximum likelihood method, the proposed method is computationally simpler, and hence easier to implement. It is robust to the violation of distributional assumption about the covariate of interest. In producing correct inference, the performance of the proposed method compared to the other competing methods has been investigated through extensive simulations. A real-life application of the method is also shown using data from a population-based case-control study of non-Hodgkin lymphoma.

Keywords: environmental exposure, detection limit, left truncation, bias, ad-hoc substitution

Procedia PDF Downloads 211