Search results for: missile approach warning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 13650

Search results for: missile approach warning

11580 Assessing Artificial Neural Network Models on Forecasting the Return of Stock Market Index

Authors: Hamid Rostami Jaz, Kamran Ameri Siahooei

Abstract:

Up to now different methods have been used to forecast the index returns and the index rate. Artificial intelligence and artificial neural networks have been one of the methods of index returns forecasting. This study attempts to carry out a comparative study on the performance of different Radial Base Neural Network and Feed-Forward Perceptron Neural Network to forecast investment returns on the index. To achieve this goal, the return on investment in Tehran Stock Exchange index is evaluated and the performance of Radial Base Neural Network and Feed-Forward Perceptron Neural Network are compared. Neural networks performance test is applied based on the least square error in two approaches of in-sample and out-of-sample. The research results show the superiority of the radial base neural network in the in-sample approach and the superiority of perceptron neural network in the out-of-sample approach.

Keywords: exchange index, forecasting, perceptron neural network, Tehran stock exchange

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11579 Damages of Highway Bridges in Thailand during the 2014-Chiang Rai Earthquake

Authors: Rajwanlop Kumpoopong, Sukit Yindeesuk, Pornchai Silarom

Abstract:

On May 5, 2014, an earthquake of magnitude 6.3 Richter hit the Northern part of Thailand. The epicenter was in Phan District, Chiang Rai Province. This earthquake or the so-called 2014-Chiang Rai Earthquake is the strongest ground shaking that Thailand has ever been experienced in her modern history. The 2014-Chiang Rai Earthquake confirms the geological evidence, which has previously been ignored by most engineers, that earthquakes of considerable magnitudes 6 to 7 Richter can occurr within the country. This promptly stimulates authorized agencies to pay more attention at the safety of their assets and promotes the comprehensive review of seismic resistance design of their building structures. The focus of this paper is to summarize the damages of highway bridges as a result of the 2014-Chiang Rai ground shaking, the remedy actions, and the research needs. The 2014-Chiang Rai Earthquake caused considerable damages to nearby structures such as houses, schools, and temples. The ground shaking, however, caused damage to only one highway bridge, Mae Laos Bridge, located several kilometers away from the epicenter. The damage of Mae Laos Bridge was in the form of concrete spalling caused by pounding of cap beam on the deck structure. The damage occurred only at the end or abutment span. The damage caused by pounding is not a surprise, but the pounding by only one bridge requires further investigation and discussion. Mae Laos Bridge is a river crossing bridge with relatively large approach structure. In as much, the approach structure is confined by strong retaining walls. This results in a rigid-like approach structure which vibrates at the acceleration approximately equal to the ground acceleration during the earthquake and exerts a huge force to the abutment causing the pounding of cap beam on the deck structure. Other bridges nearby have relatively small approach structures, and therefore have no capability to generate pounding. The effect of mass of the approach structure on pounding of cap beam on the deck structure is also evident by the damage of one pedestrian bridge in front of Thanthong Wittaya School located 50 meters from Mae Laos Bridge. The width of the approach stair of this bridge is wider than the typical one to accommodate the stream of students during pre- and post-school times. This results in a relatively large mass of the approach stair which in turn exerts a huge force to the pier causing pounding of cap beam on the deck structure during ground shaking. No sign of pounding was observed for a typical pedestrian bridge located at another end of Mae Laos Bridge. Although pounding of cap beam on the deck structure of the above mentioned bridges does not cause serious damage to bridge structure, this incident promotes the comprehensive review of seismic resistance design of highway bridges in Thailand. Given a proper mass and confinement of the approach structure, the pounding of cap beam on the deck structure can be easily excited even at the low to moderate ground shaking. In as much, if the ground shaking becomes stronger, the pounding is certainly more powerful. This may cause the deck structure to be unseated and fall off in the case of unrestrained bridge. For the bridge with restrainer between cap beam and the deck structure, the restrainer may prevent the deck structure from falling off. However, preventing free movement of the pier by the restrainer may damage the pier itself. Most highway bridges in Thailand have dowel bars embedded connecting cap beam and the deck structure. The purpose of the existence of dowel bars is, however, not intended for any seismic resistance. Their ability to prevent the deck structure from unseating and their effect on the potential damage of the pier should be evaluated. In response to this expected situation, Thailand Department of Highways (DOH) has set up a team to revise the standard practices for the seismic resistance design of highway bridges in Thailand. In addition, DOH has also funded the research project 'Seismic Resistance Evaluation of Pre- and Post-Design Modifications of DOH’s Bridges' with the scope of full-scale tests of single span bridges under reversed cyclic static loadings for both longitudinal and transverse directions and computer simulations to evaluate the seismic performance of the existing bridges and the design modification bridges. The research is expected to start in October, 2015.

Keywords: earthquake, highway bridge, Thailand, damage, pounding, seismic resistance

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11578 Design Standardization in Aramco: Strategic Analysis

Authors: Mujahid S. Alharbi

Abstract:

The construction of process plants in oil and gas-producing countries, such as Saudi Arabia, necessitates substantial investment in design and building. Each new plant, while unique, includes common building types, suggesting an opportunity for design standardization. This study investigates the adoption of standardized Issue For Construction (IFC) packages for non-process buildings in Saudi Aramco. A SWOT analysis presents the strengths, weaknesses, opportunities, and threats of this approach. The approach's benefits are illustrated using the Hawiyah Unayzah Gas Reservoir Storage Program (HUGRSP) as a case study. Standardization not only offers significant cost savings and operational efficiencies but also expedites project timelines, reduces the potential for change orders, and fosters local economic growth by allocating building tasks to local contractors. Standardization also improves project management by easing interface constraints between different contractors and promoting adaptability to future industry changes. This research underscores the standardization of non-process buildings as a powerful strategy for cost optimization, efficiency enhancement, and local economic development in process plant construction within the oil and gas sector.

Keywords: building, construction, management, project, standardization

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11577 Learning the Most Common Causes of Major Industrial Accidents and Apply Best Practices to Prevent Such Accidents

Authors: Rajender Dahiya

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Investigation outcomes of major process incidents have been consistent for decades and validate that the causes and consequences are often identical. The debate remains as we continue to experience similar process incidents even with enormous development of new tools, technologies, industry standards, codes, regulations, and learning processes? The objective of this paper is to investigate the most common causes of major industrial incidents and reveal industry challenges and best practices to prevent such incidents. The author, in his current role, performs audits and inspections of a variety of high-hazard industries in North America, including petroleum refineries, chemicals, petrochemicals, manufacturing, etc. In this paper, he shares real life scenarios, examples, and case studies from high hazards operating facilities including key challenges and best practices. This case study will provide a clear understanding of the importance of near miss incident investigation. The incident was a Safe operating limit excursion. The case describes the deficiencies in management programs, the competency of employees, and the culture of the corporation that includes hazard identification and risk assessment, maintaining the integrity of safety-critical equipment, operating discipline, learning from process safety near misses, process safety competency, process safety culture, audits, and performance measurement. Failure to identify the hazards and manage the risks of highly hazardous materials and processes is one of the primary root-causes of an incident, and failure to learn from past incidents is the leading cause of the recurrence of incidents. Several investigations of major incidents discovered that each showed several warning signs before occurring, and most importantly, all were preventable. The author will discuss why preventable incidents were not prevented and review the mutual causes of learning failures from past major incidents. The leading causes of past incidents are summarized below. Management failure to identify the hazard and/or mitigate the risk of hazardous processes or materials. This process starts early in the project stage and continues throughout the life cycle of the facility. For example, a poorly done hazard study such as HAZID, PHA, or LOPA is one of the leading causes of the failure. If this step is performed correctly, then the next potential cause is. Management failure to maintain the integrity of safety critical systems and equipment. In most of the incidents, mechanical integrity of the critical equipment was not maintained, safety barriers were either bypassed, disabled, or not maintained. The third major cause is Management failure to learn and/or apply learning from the past incidents. There were several precursors before those incidents. These precursors were either ignored altogether or not taken seriously. This paper will conclude by sharing how a well-implemented operating management system, good process safety culture, and competent leaders and staff contributed to managing the risks to prevent major incidents.

Keywords: incident investigation, risk management, loss prevention, process safety, accident prevention

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11576 Aryne Mediated, Transition-Metal Free Arylations of Quinolines for Medicinal and Materials Applications

Authors: Rakesh Kumar, Shashi Janeoo, Ankit Dhiman, Siddharth Chopra

Abstract:

Arynes are versatile reactive intermediates that offer broad opportunities in green organic synthesis. Arynes are potential aryl group surrogates for the transition metal-free environment friendly arylation reactions. Regioselective arylations of quinolines were achieved by the reactions of quinoline N-oxides with aryne intermediates generated in situ from the Kobayashi precursors. Various 2-substituted quinolines provided 3-arylated-2-substituted quinolines under ambient conditions. Acridine N-oxides also reacted well and provided unusual 4-arylacridines. Various fluorine containing 2,3-diarylquinaolines prepared using this approach were evaluated for antibacterial activity and two compounds inhibited the drug-resistant strains of S-aureus with a good selectivity index. Further, the 2,3-diarylquinolines as the potential optoelectronic materials were prepared by the aryne chemistry approach and their optical and electronic properties for such applications are under study. The aryne intermediates provide an effective Green Chemistry tool to achieve versatile arylated heteroarenes for diverse applications.

Keywords: arynes, arylation, quinolines, acridines.

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11575 A Comparative Study between Japan and the European Union on Software Vulnerability Public Policies

Authors: Stefano Fantin

Abstract:

The present analysis outcomes from the research undertaken in the course of the European-funded project EUNITY, which targets the gaps in research and development on cybersecurity and privacy between Europe and Japan. Under these auspices, the research presents a study on the policy approach of Japan, the EU and a number of Member States of the Union with regard to the handling and discovery of software vulnerabilities, with the aim of identifying methodological differences and similarities. This research builds upon a functional comparative analysis of both public policies and legal instruments from the identified jurisdictions. The result of this analysis is based on semi-structured interviews with EUNITY partners, as well as by the participation of the researcher to a recent report from the Center for EU Policy Study on software vulnerability. The European Union presents a rather fragmented legal framework on software vulnerabilities. The presence of a number of different legislations at the EU level (including Network and Information Security Directive, Critical Infrastructure Directive, Directive on the Attacks at Information Systems and the Proposal for a Cybersecurity Act) with no clear focus on such a subject makes it difficult for both national governments and end-users (software owners, researchers and private citizens) to gain a clear understanding of the Union’s approach. Additionally, the current data protection reform package (general data protection regulation), seems to create legal uncertainty around security research. To date, at the member states level, a few efforts towards transparent practices have been made, namely by the Netherlands, France, and Latvia. This research will explain what policy approach such countries have taken. Japan has started implementing a coordinated vulnerability disclosure policy in 2004. To date, two amendments can be registered on the framework (2014 and 2017). The framework is furthermore complemented by a series of instruments allowing researchers to disclose responsibly any new discovery. However, the policy has started to lose its efficiency due to a significant increase in reports made to the authority in charge. To conclude, the research conducted reveals two asymmetric policy approaches, time-wise and content-wise. The analysis therein will, therefore, conclude with a series of policy recommendations based on the lessons learned from both regions, towards a common approach to the security of European and Japanese markets, industries and citizens.

Keywords: cybersecurity, vulnerability, European Union, Japan

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11574 A Digital Twin Approach for Sustainable Territories Planning: A Case Study on District Heating

Authors: Ahmed Amrani, Oussama Allali, Amira Ben Hamida, Felix Defrance, Stephanie Morland, Eva Pineau, Thomas Lacroix

Abstract:

The energy planning process is a very complex task that involves several stakeholders and requires the consideration of several local and global factors and constraints. In order to optimize and simplify this process, we propose a tool-based iterative approach applied to district heating planning. We build our tool with the collaboration of a French territory using actual district data and implementing the European incentives. We set up an iterative process including data visualization and analysis, identification and extraction of information related to the area concerned by the operation, design of sustainable planning scenarios leveraging local renewable and recoverable energy sources, and finally, the evaluation of scenarios. The last step is performed by a dynamic digital twin replica of the city. Territory’s energy experts confirm that the tool provides them with valuable support towards sustainable energy planning.

Keywords: climate change, data management, decision support, digital twin, district heating, energy planning, renewables, smart city

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11573 Improvement of Direct Torque and Flux Control of Dual Stator Induction Motor Drive Using Intelligent Techniques

Authors: Kouzi Katia

Abstract:

This paper proposes a Direct Torque Control (DTC) algorithm of dual Stator Induction Motor (DSIM) drive using two approach intelligent techniques: Artificial Neural Network (ANN) approach replaces the switching table selector block of conventional DTC and Mamdani Fuzzy Logic controller (FLC) is used for stator resistance estimation. The fuzzy estimation method is based on an online stator resistance correction through the variations of stator current estimation error and its variation. The fuzzy logic controller gives the future stator resistance increment at the output. The main advantage of suggested algorithm control is to reduce the hardware complexity of conventional selectors, to avoid the drive instability that may occur in certain situation and ensure the tracking of the actual of the stator resistance. The effectiveness of the technique and the improvement of the whole system performance are proved by results.

Keywords: artificial neural network, direct torque control, dual stator induction motor, fuzzy logic estimator, switching table

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11572 Privacy Concerns and Law Enforcement Data Collection to Tackle Domestic and Sexual Violence

Authors: Francesca Radice

Abstract:

Domestic and sexual violence provokes, on average in Australia, one female death per week due to intimate violence behaviours. 83% of couples meet online, and intercepting domestic and sexual violence at this level would be beneficial. It has been observed that violent or coercive behaviour has been apparent from initial conversations on dating apps like Tinder. Child pornography, stalking, and coercive control are some criminal offences from dating apps, including women murdered after finding partners through Tinder. Police databases and predictive policing are novel approaches taken to prevent crime before harm is done. This research will investigate how police databases can be used in a privacy-preserving way to characterise users in terms of their potential for violent crime. Using the COPS database of NSW Police, we will explore how the past criminal record can be interpreted to yield a category of potential danger for each dating app user. It is up to the judgement of each subscriber on what degree of the potential danger they are prepared to enter into. Sentiment analysis is an area where research into natural language processing has made great progress over the last decade. This research will investigate how sentiment analysis can be used to interpret interchanges between dating app users to detect manipulative or coercive sentiments. These can be used to alert law enforcement if continued for a defined number of communications. One of the potential problems of this approach is the potential prejudice a categorisation can cause. Another drawback is the possibility of misinterpreting communications and involving law enforcement without reason. The approach will be thoroughly tested with cross-checks by human readers who verify both the level of danger predicted by the interpretation of the criminal record and the sentiment detected from personal messages. Even if only a few violent crimes can be prevented, the approach will have a tangible value for real people.

Keywords: sentiment analysis, data mining, predictive policing, virtual manipulation

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11571 3D Elasticity Analysis of Laminated Composite Plate Using State Space Method

Authors: Prathmesh Vikas Patil, Yashaswini Lomte Patil

Abstract:

Laminated composite materials have considerable attention in various engineering applications due to their exceptional strength-to-weight ratio and mechanical properties. The analysis of laminated composite plates in three-dimensional (3D) elasticity is a complex problem, as it requires accounting for the orthotropic anisotropic nature of the material and the interactions between multiple layers. Conventional approaches, such as the classical plate theory, provide simplified solutions but are limited in performing exact analysis of the plate. To address such a challenge, the state space method emerges as a powerful numerical technique for modeling the behavior of laminated composites in 3D. The state-space method involves transforming the governing equations of elasticity into a state-space representation, enabling the analysis of complex structural systems in a systematic manner. Here, an effort is made to perform a 3D elasticity analysis of plates with cross-ply and angle-ply laminates using the state space approach. The state space approach is used in this study as it is a mixed formulation technique that gives the displacements and stresses simultaneously with the same level of accuracy.

Keywords: cross ply laminates, angle ply laminates, state space method, three-dimensional elasticity analysis

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11570 Identification of Thermally Critical Zones Based on Inter Seasonal Variation in Temperature

Authors: Sakti Mandal

Abstract:

Varying distribution of land surface temperature in an urbanized environment is a globally addressed phenomenon. Usually has been noticed that criticality of surface temperature increases from the periphery to the urban centre. As the centre experiences maximum severity of heat throughout the year, it also represents most critical zone in terms of thermal condition. In this present study, an attempt has been taken to propose a quantitative approach of thermal critical zonation (TCZ) on the basis of seasonal temperature variation. Here the zonation is done by calculating thermal critical value (TCV). From the Landsat 8 thermal digital data of summer and winter seasons for the year 2014, the land surface temperature maps and thermally critical zonation has been prepared, and corresponding dataset has been computed to conduct the overall study of that particular study area. It is shown that TCZ can be clearly identified and analyzed by the help of inter-seasonal temperature range. The results of this study can be utilized effectively in future urban development and planning projects as well as a framework for implementing rules and regulations by the authorities for a sustainable urban development through an environmentally affable approach.

Keywords: thermal critical values (TCV), thermally critical zonation (TCZ), land surface temperature (LST), Landsat 8, Kolkata Municipal Corporation (KMC)

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11569 Radiomics: Approach to Enable Early Diagnosis of Non-Specific Breast Nodules in Contrast-Enhanced Magnetic Resonance Imaging

Authors: N. D'Amico, E. Grossi, B. Colombo, F. Rigiroli, M. Buscema, D. Fazzini, G. Cornalba, S. Papa

Abstract:

Purpose: To characterize, through a radiomic approach, the nature of nodules considered non-specific by expert radiologists, recognized in magnetic resonance mammography (MRm) with T1-weighted (T1w) sequences with paramagnetic contrast. Material and Methods: 47 cases out of 1200 undergoing MRm, in which the MRm assessment gave uncertain classification (non-specific nodules), were admitted to the study. The clinical outcome of the non-specific nodules was later found through follow-up or further exams (biopsy), finding 35 benign and 12 malignant. All MR Images were acquired at 1.5T, a first basal T1w sequence and then four T1w acquisitions after the paramagnetic contrast injection. After a manual segmentation of the lesions, done by a radiologist, and the extraction of 150 radiomic features (30 features per 5 subsequent times) a machine learning (ML) approach was used. An evolutionary algorithm (TWIST system based on KNN algorithm) was used to subdivide the dataset into training and validation test and to select features yielding the maximal amount of information. After this pre-processing, different machine learning systems were applied to develop a predictive model based on a training-testing crossover procedure. 10 cases with a benign nodule (follow-up older than 5 years) and 18 with an evident malignant tumor (clear malignant histological exam) were added to the dataset in order to allow the ML system to better learn from data. Results: NaiveBayes algorithm working on 79 features selected by a TWIST system, resulted to be the best performing ML system with a sensitivity of 96% and a specificity of 78% and a global accuracy of 87% (average values of two training-testing procedures ab-ba). The results showed that in the subset of 47 non-specific nodules, the algorithm predicted the outcome of 45 nodules which an expert radiologist could not identify. Conclusion: In this pilot study we identified a radiomic approach allowing ML systems to perform well in the diagnosis of a non-specific nodule at MR mammography. This algorithm could be a great support for the early diagnosis of malignant breast tumor, in the event the radiologist is not able to identify the kind of lesion and reduces the necessity for long follow-up. Clinical Relevance: This machine learning algorithm could be essential to support the radiologist in early diagnosis of non-specific nodules, in order to avoid strenuous follow-up and painful biopsy for the patient.

Keywords: breast, machine learning, MRI, radiomics

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11568 Managing Incomplete PSA Observations in Prostate Cancer Data: Key Strategies and Best Practices for Handling Loss to Follow-Up and Missing Data

Authors: Madiha Liaqat, Rehan Ahmed Khan, Shahid Kamal

Abstract:

Multiple imputation with delta adjustment is a versatile and transparent technique for addressing univariate missing data in the presence of various missing mechanisms. This approach allows for the exploration of sensitivity to the missing-at-random (MAR) assumption. In this review, we outline the delta-adjustment procedure and illustrate its application for assessing the sensitivity to deviations from the MAR assumption. By examining diverse missingness scenarios and conducting sensitivity analyses, we gain valuable insights into the implications of missing data on our analyses, enhancing the reliability of our study's conclusions. In our study, we focused on assessing logPSA, a continuous biomarker in incomplete prostate cancer data, to examine the robustness of conclusions against plausible departures from the MAR assumption. We introduced several approaches for conducting sensitivity analyses, illustrating their application within the pattern mixture model (PMM) under the delta adjustment framework. This proposed approach effectively handles missing data, particularly loss to follow-up.

Keywords: loss to follow-up, incomplete response, multiple imputation, sensitivity analysis, prostate cancer

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11567 Engagement Analysis Using DAiSEE Dataset

Authors: Naman Solanki, Souraj Mondal

Abstract:

With the world moving towards online communication, the video datastore has exploded in the past few years. Consequently, it has become crucial to analyse participant’s engagement levels in online communication videos. Engagement prediction of people in videos can be useful in many domains, like education, client meetings, dating, etc. Video-level or frame-level prediction of engagement for a user involves the development of robust models that can capture facial micro-emotions efficiently. For the development of an engagement prediction model, it is necessary to have a widely-accepted standard dataset for engagement analysis. DAiSEE is one of the datasets which consist of in-the-wild data and has a gold standard annotation for engagement prediction. Earlier research done using the DAiSEE dataset involved training and testing standard models like CNN-based models, but the results were not satisfactory according to industry standards. In this paper, a multi-level classification approach has been introduced to create a more robust model for engagement analysis using the DAiSEE dataset. This approach has recorded testing accuracies of 0.638, 0.7728, 0.8195, and 0.866 for predicting boredom level, engagement level, confusion level, and frustration level, respectively.

Keywords: computer vision, engagement prediction, deep learning, multi-level classification

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11566 The Approach to Develop Value Chain to Enhance the Management Efficiency of Thai Tour Operators in Order to Support Free Trade within the Framework of ASEAN Cooperation

Authors: Yalisa Tonsorn

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The objectives of this study are 1) to study the readiness of Thai tour operators in order to prepare for being ASEAN members, 2) to study opportunity and obstacles of the management of Thai tour operators, and 3) to find approach for developing value chain in order to enhance the management efficiency of Thai tour operators in order to support free trade within the framework of ASEAN cooperation. The research methodology is mixed between qualitative method and quantitative method. In-depth interview was done with key informants, including management supervisors, medium managers, and officers of the travel agencies. The questionnaire was conducted with 300 sampling. According to the study, it was found that the approach for developing value chain to enhance the management efficiency of Thai travel agencies in order to support free trade within the framework of ASEAN cooperation, the tour operators must give priority to the customer and deliver the service exceeding the customer’s expectation. There are 2 groups of customers: 1) external customers referring to tourist, and 2) internal customers referring to staff who deliver the service to the customers, including supervisors, colleagues, or subordinates. There are 2 issues which need to be developed: 1) human resource development in order to cultivate the working concept by focusing on importance of customers, and excellent service providing, and 2) working system development by building value and innovation in operational process including services to the company in order to deliver the highest impressive service to both internal and external customers. Moreover, the tour operators could support the increased number of tourists significantly. This could enhance the capacity of the business and affect the increase of competition capability in the economic dimension of the country.

Keywords: AEC (ASEAN Economic Eommunity), core activities, support activities, values chain

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11565 Evaluation of Two DNA Extraction Methods for Minimal Porcine (Pork) Detection in Halal Food Sample Mixture Using Taqman Real-time PCR Technique

Authors: Duaa Mughal, Syeda Areeba Nadeem, Shakil Ahmed, Ishtiaq Ahmed Khan

Abstract:

The identification of porcine DNA in Halal food items is critical to ensuring compliance with dietary restrictions and religious beliefs. In Islam, Porcine is prohibited as clearly mentioned in Quran (Surah Al-Baqrah, Ayat 173). The purpose of this study was to compare two DNA extraction procedures for detecting 0.001% of porcine DNA in processed Halal food sample mixtures containing chicken, camel, veal, turkey and goat meat using the TaqMan Real-Time PCR technology. In this research, two different commercial kit protocols were compared. The processed sample mixtures were prepared by spiking known concentration of porcine DNA to non-porcine food matrices. Afterwards, TaqMan Real-Time PCR technique was used to target a particular porcine gene from the extracted DNA samples, which was quantified after extraction. The results of the amplification were evaluated for sensitivity, specificity, and reproducibility. The results of the study demonstrated that two DNA extraction techniques can detect 0.01% of porcine DNA in mixture of Halal food samples. However, as compared to the alternative approach, Eurofins| GeneScan GeneSpin DNA Isolation kit showed more effective sensitivity and specificity. Furthermore, the commercial kit-based approach showed great repeatability with minimal variance across repeats. Quantification of DNA was done by using fluorometric assay. In conclusion, the comparison of DNA extraction methods for detecting porcine DNA in Halal food sample mixes using the TaqMan Real-Time PCR technology reveals that the commercial kit-based approach outperforms the other methods in terms of sensitivity, specificity, and repeatability. This research helps to promote the development of reliable and standardized techniques for detecting porcine DNA in Halal food items, religious conformity and assuring nutritional.

Keywords: real time PCR (qPCR), DNA extraction, porcine DNA, halal food authentication, religious conformity

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11564 MBR-RO System Operation in Quantitative and Qualitative Promotion of Waste Water Cleaning: Case Study of Shokohieyh Qoms’ Waste Water Cleaning

Authors: A. A. Hassani, M. Nasri Nasrabadi

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According to population growth and increasing water needs of industrial and agricultural sections and lack of existing water sources, also increases of wastewater and new wastewater treatment plant construction’s high costs, it is inevitable to reuse wastewater with the approach of increasing wastewater treatment capacity and output sewage quality. In this regard, the first sewage reuse plan in industrial uses was designed with the approach of qualitative and quantitative improvement due to the increased organic load of the output sewage of Qom Shokohieh city’s’ in wastewater treatment plant. This research investigated qualitative factors COD, BOD, TSS, TDS, and input and output heavy metal of MBR-RO system and ability of increase wastewater acceptance capacity by existing in wastewater treatment plant. For this purpose, experimental results of seven-month navigation system have been used from 07/01/2013 to 02/01/2014. Existing data analysis showed that MBR system is able to remove 93.2% COD, 94.4% BOD, 13.8% TDS, 98% heavy metals and RO system is able to remove 98.9% TDS. This study showed that MBR-RO integration system is able to increase the capacity of refinery by 30%.

Keywords: industrial wastewater, wastewater reuse, MBR, RO

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11563 A Minimally Invasive Approach Using Bio-Miniatures Implant System for Full Arch Rehabilitation

Authors: Omid Allan

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The advent of ultra-narrow diameter implants initially offered an alternative to wider conventional implants. However, their design limitations have restricted their applicability primarily to overdentures and cement-retained fixed prostheses, often with unpredictable long-term outcomes. The introduction of the new Miniature Implants has revolutionized the field of implant dentistry, leading to a more streamlined approach. The utilization of Miniature Implants has emerged as a promising alternative to the traditional approach that entails the traumatic sequential bone drilling procedures and the use of conventional implants for full and partial arch restorations. The innovative "BioMiniatures Implant System serves as a groundbreaking bridge connecting mini implants with standard implant systems. This system allows practitioners to harness the advantages of ultra-small implants, enabling minimally invasive insertion and facilitating the application of fixed screw-retained prostheses, which were only available to conventional wider implant systems. This approach streamlines full and partial arch rehabilitation with minimal or even no bone drilling, significantly reducing surgical risks and complications for clinicians while minimizing patient morbidity. The ultra-narrow diameter and self-advancing features of these implants eliminate the need for invasive and technically complex procedures such as bone augmentation and guided bone regeneration (GBR), particularly in cases involving thin alveolar ridges. Furthermore, the absence of a microcap between the implant and abutment eliminates the potential for micro-leakage and micro-pumping effects, effectively mitigating the risk of marginal bone loss and future peri-implantitis. The cumulative experience of restoring over 50 full and partial arch edentulous cases with this system has yielded an outstanding success rate exceeding 97%. The long-term success with a stable marginal bone level in the study firmly establishes these implants as a dependable alternative to conventional implants, especially for full arch rehabilitation cases. Full arch rehabilitation with these implants holds the promise of providing a simplified solution for edentulous patients who typically present with atrophic narrow alveolar ridges, eliminating the need for extensive GBR and bone augmentation to restore their dentition with fixed prostheses.

Keywords: mini-implant, biominiatures, miniature implants, minimally invasive dentistry, full arch rehabilitation

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11562 Logistic Model Tree and Expectation-Maximization for Pollen Recognition and Grouping

Authors: Endrick Barnacin, Jean-Luc Henry, Jack Molinié, Jimmy Nagau, Hélène Delatte, Gérard Lebreton

Abstract:

Palynology is a field of interest for many disciplines. It has multiple applications such as chronological dating, climatology, allergy treatment, and even honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time-consuming task that requires the intervention of experts in the field, which is becoming increasingly rare due to economic and social conditions. So, the automation of this task is a necessity. Pollen slides analysis is mainly a visual process as it is carried out with the naked eye. That is the reason why a primary method to automate palynology is the use of digital image processing. This method presents the lowest cost and has relatively good accuracy in pollen retrieval. In this work, we propose a system combining recognition and grouping of pollen. It consists of using a Logistic Model Tree to classify pollen already known by the proposed system while detecting any unknown species. Then, the unknown pollen species are divided using a cluster-based approach. Success rates for the recognition of known species have been achieved, and automated clustering seems to be a promising approach.

Keywords: pollen recognition, logistic model tree, expectation-maximization, local binary pattern

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11561 Exploration of RFID in Healthcare: A Data Mining Approach

Authors: Shilpa Balan

Abstract:

Radio Frequency Identification, also popularly known as RFID is used to automatically identify and track tags attached to items. This study focuses on the application of RFID in healthcare. The adoption of RFID in healthcare is a crucial technology to patient safety and inventory management. Data from RFID tags are used to identify the locations of patients and inventory in real time. Medical errors are thought to be a prominent cause of loss of life and injury. The major advantage of RFID application in healthcare industry is the reduction of medical errors. The healthcare industry has generated huge amounts of data. By discovering patterns and trends within the data, big data analytics can help improve patient care and lower healthcare costs. The number of increasing research publications leading to innovations in RFID applications shows the importance of this technology. This study explores the current state of research of RFID in healthcare using a text mining approach. No study has been performed yet on examining the current state of RFID research in healthcare using a data mining approach. In this study, related articles were collected on RFID from healthcare journal and news articles. Articles collected were from the year 2000 to 2015. Significant keywords on the topic of focus are identified and analyzed using open source data analytics software such as Rapid Miner. These analytical tools help extract pertinent information from massive volumes of data. It is seen that the main benefits of adopting RFID technology in healthcare include tracking medicines and equipment, upholding patient safety, and security improvement. The real-time tracking features of RFID allows for enhanced supply chain management. By productively using big data, healthcare organizations can gain significant benefits. Big data analytics in healthcare enables improved decisions by extracting insights from large volumes of data.

Keywords: RFID, data mining, data analysis, healthcare

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11560 Re-Conceptualizing the Indigenous Learning Space for Children in Bangladesh Placing Built Environment as Third Teacher

Authors: Md. Mahamud Hassan, Shantanu Biswas Linkon, Nur Mohammad Khan

Abstract:

Over the last three decades, the primary education system in Bangladesh has experienced significant improvement, but it has failed to cope with different social and cultural aspects, which present many challenges for children, families, and the public school system. Neglecting our own contextual learning environment, it is a matter of sorrow that much attention has been paid to the more physical outcome-focused model, which is nothing but mere infrastructural development, and less subtle to the environment that suits the child's psychology and improves their social, emotional, physical, and moral competency. In South Asia, the symbol of education was never the little red house of colonial architecture but “A Guru sitting under a tree", whereas a responsive and inclusive design approach could help to create more innovative learning environments. Such an approach incorporates how the built, natural, and cultural environment shapes the learner; in turn, learners shape the learning. This research will be conducted to, i) identify the major issues and drawbacks of government policy for primary education development programs; ii) explore and evaluate the morphology of the conventional model of school, and iii) propose an alternative model in a collaborative design process with the stakeholders for maximizing the relationship between the physical learning environments and learners by treating “the built environment” as “the third teacher.” Based on observation, this research will try to find out to what extent built, and natural environments can be utilized as a teaching tool for a more optimal learning environment. It should also be evident that there is a significant gap in the state policy, predetermined educational specifications, and implementation process in response to stakeholders’ involvement. The outcome of this research will contribute to a people-place sensitive design approach through a more thoughtful and responsive architectural process.

Keywords: built environment, conventional planning, indigenous learning space, responsive design

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11559 Prep: Pause, Reset, Establish Expectations, and Proceed. A Practical Approach for Classroom Transitions

Authors: Shane-Anthony Smith

Abstract:

Teachers across grade levels and content areas face a myriad of challenges in the classroom. From inconsistent attendance to disruptive behaviors, these challenges can have a dire impact on the educational space, untimely leading to a loss of instructional time and student disenfranchisement from learning. While these challenges are not new to the educational landscape, the post-COVID classroom has, in many instances, been more severely impacted by behaviors that are not conducive to learning. Despite the mounting challenges, the role of the teacher remains unchanged - that is, to create and maintain a safe environment that is conducive to learning and promotes successful learning outcomes. Accomplishing this feat is no easy task. Yet, there are steps teachers can - indeed, must - take to better set themselves and their students up for success. The key to achieving this success is effective classroom transitions. This paper presents a four-step approach for teachers to engage in successful classroom transitions to promote meaningful student engagement and active positive learning outcomes. The transition strategy I will explore is called PREP (Pause, Reset, Establish Expectations, and Proceed). I developed this strategy in my work as a Residency Director for my university’s teacher residency program. In this role, I am tasked with coaching emerging teachers and their in-service teaching mentors in the field, as well as providing mentorship to special education resident teachers pursuing teaching degrees in the program. As a teacher educator, being in Middle and High school classrooms provides an intricate and critical understanding of the challenges, opportunities, and possibilities in the classroom. For this paper, I will explore how teachers can optimize the opportunities PREP provides to keep students engaged and, thus, improve student achievement. I will describe the approach, explain its use, and provide case-study examples of its classroom application.

Keywords: classroom management, teaching strategies, student engagement, classroom transition

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11558 Machine Learning in Momentum Strategies

Authors: Yi-Min Lan, Hung-Wen Cheng, Hsuan-Ling Chang, Jou-Ping Yu

Abstract:

The study applies machine learning models to construct momentum strategies and utilizes the information coefficient as an indicator for selecting stocks with strong and weak momentum characteristics. Through this approach, the study has built investment portfolios capable of generating superior returns and conducted a thorough analysis. Compared to existing research on momentum strategies, machine learning is incorporated to capture non-linear interactions. This approach enhances the conventional stock selection process, which is often impeded by difficulties associated with timeliness, accuracy, and efficiency due to market risk factors. The study finds that implementing bidirectional momentum strategies outperforms unidirectional ones, and momentum factors with longer observation periods exhibit stronger correlations with returns. Optimizing the number of stocks in the portfolio while staying within a certain threshold leads to the highest level of excess returns. The study presents a novel framework for momentum strategies that enhances and improves the operational aspects of asset management. By introducing innovative financial technology applications to traditional investment strategies, this paper can demonstrate significant effectiveness.

Keywords: information coefficient, machine learning, momentum, portfolio, return prediction

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11557 Implementing Quality Improvement Projects to Enhance Contraception and Abortion Care Service Provision and Pre-Service Training of Health Care Providers

Authors: Munir Kassa, Mengistu Hailemariam, Meghan Obermeyer, Kefelegn Baruda, Yonas Getachew, Asnakech Dessie

Abstract:

Improving the quality of sexual and reproductive health services that women receive is expected to have an impact on women’s satisfaction with the services, on their continued use and, ultimately, on their ability to achieve their fertility goals or reproductive intentions. Surprisingly, however, there is little empirical evidence of either whether this expectation is correct, or how best to improve service quality within sexual and reproductive health programs so that these impacts can be achieved. The Recent focus on quality has prompted more physicians to do quality improvement work, but often without the needed skill sets, which results in poorly conceived and ultimately unsuccessful improvement initiatives. As this renders the work unpublishable, it further impedes progress in the field of health care improvement and widens the quality chasm. Moreover, since 2014, the Center for International Reproductive Health Training (CIRHT) has worked diligently with 11 teaching hospitals across Ethiopia to increase access to contraception and abortion care services. This work has included improving pre-service training through education and curriculum development, expanding hands-on training to better learn critical techniques and counseling skills, and fostering a “team science” approach to research by encouraging scientific exploration. This is the first time this systematic approach has been applied and documented to improve access to high-quality services in Ethiopia. The purpose of this article is to report initiatives undertaken, and findings concluded by the clinical service team at CIRHT in an effort to provide a pragmatic approach to quality improvement projects. An audit containing nearly 300 questions about several aspects of patient care, including structure, process, and outcome indicators was completed by each teaching hospital’s quality improvement team. This baseline audit assisted in identifying major gaps and barriers, and each team was responsible for determining specific quality improvement aims and tasks to support change interventions using Shewart’s Cycle for Learning and Improvement (the Plan-Do-Study-Act model). To measure progress over time, quality improvement teams met biweekly and compiled monthly data for review. Also, site visits to each hospital were completed by the clinical service team to ensure monitoring and support. The results indicate that applying an evidence-based, participatory approach to quality improvement has the potential to increase the accessibility and quality of services in a short amount of time. In addition, continued ownership and on-site support are vital in promoting sustainability. This approach could be adapted and applied in similar contexts, particularly in other African countries.

Keywords: abortion, contraception, quality improvement, service provision

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11556 Human Identification and Detection of Suspicious Incidents Based on Outfit Colors: Image Processing Approach in CCTV Videos

Authors: Thilini M. Yatanwala

Abstract:

CCTV (Closed-Circuit-Television) Surveillance System is being used in public places over decades and a large variety of data is being produced every moment. However, most of the CCTV data is stored in isolation without having integrity. As a result, identification of the behavior of suspicious people along with their location has become strenuous. This research was conducted to acquire more accurate and reliable timely information from the CCTV video records. The implemented system can identify human objects in public places based on outfit colors. Inter-process communication technologies were used to implement the CCTV camera network to track people in the premises. The research was conducted in three stages and in the first stage human objects were filtered from other movable objects available in public places. In the second stage people were uniquely identified based on their outfit colors and in the third stage an individual was continuously tracked in the CCTV network. A face detection algorithm was implemented using cascade classifier based on the training model to detect human objects. HAAR feature based two-dimensional convolution operator was introduced to identify features of the human face such as region of eyes, region of nose and bridge of the nose based on darkness and lightness of facial area. In the second stage outfit colors of human objects were analyzed by dividing the area into upper left, upper right, lower left, lower right of the body. Mean color, mod color and standard deviation of each area were extracted as crucial factors to uniquely identify human object using histogram based approach. Color based measurements were written in to XML files and separate directories were maintained to store XML files related to each camera according to time stamp. As the third stage of the approach, inter-process communication techniques were used to implement an acknowledgement based CCTV camera network to continuously track individuals in a network of cameras. Real time analysis of XML files generated in each camera can determine the path of individual to monitor full activity sequence. Higher efficiency was achieved by sending and receiving acknowledgments only among adjacent cameras. Suspicious incidents such as a person staying in a sensitive area for a longer period or a person disappeared from the camera coverage can be detected in this approach. The system was tested for 150 people with the accuracy level of 82%. However, this approach was unable to produce expected results in the presence of group of people wearing similar type of outfits. This approach can be applied to any existing camera network without changing the physical arrangement of CCTV cameras. The study of human identification and suspicious incident detection using outfit color analysis can achieve higher level of accuracy and the project will be continued by integrating motion and gait feature analysis techniques to derive more information from CCTV videos.

Keywords: CCTV surveillance, human detection and identification, image processing, inter-process communication, security, suspicious detection

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11555 New Approach for Minimizing Wavelength Fragmentation in Wavelength-Routed WDM Networks

Authors: Sami Baraketi, Jean Marie Garcia, Olivier Brun

Abstract:

Wavelength Division Multiplexing (WDM) is the dominant transport technology used in numerous high capacity backbone networks, based on optical infrastructures. Given the importance of costs (CapEx and OpEx) associated to these networks, resource management is becoming increasingly important, especially how the optical circuits, called “lightpaths”, are routed throughout the network. This requires the use of efficient algorithms which provide routing strategies with the lowest cost. We focus on the lightpath routing and wavelength assignment problem, known as the RWA problem, while optimizing wavelength fragmentation over the network. Wavelength fragmentation poses a serious challenge for network operators since it leads to the misuse of the wavelength spectrum, and then to the refusal of new lightpath requests. In this paper, we first establish a new Integer Linear Program (ILP) for the problem based on a node-link formulation. This formulation is based on a multilayer approach where the original network is decomposed into several network layers, each corresponding to a wavelength. Furthermore, we propose an efficient heuristic for the problem based on a greedy algorithm followed by a post-treatment procedure. The obtained results show that the optimal solution is often reached. We also compare our results with those of other RWA heuristic methods.

Keywords: WDM, lightpath, RWA, wavelength fragmentation, optimization, linear programming, heuristic

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11554 The Need for a One Health and Welfare Approach to Industrial Animal Farming

Authors: Clinton Adas

Abstract:

Industrial animal farming contributes to numerous problems that humans face, and among these, antimicrobial resistance (AMR) has been identified by the World Health Organisation as a real possibility for the 21st Century. While numerous factors contribute to AMR, one of them is industrial animal farming and its effect on the food chain and environment. In 2017, livestock were given around 73% of all antibiotics worldwide to make them grow faster for profit purposes, to prevent illness caused by unhealthy living conditions, and to treat disease when it breaks out. Many of the antibiotics used provide little benefit to animals, and most are the same as those used by humans - including many deemed critical to human health that should be used sparingly. AMR contributes to millions of illnesses, and in 2019 was responsible for around 4.95 million deaths worldwide. It costs Europe around nine billion euros per year, while it costs the United States (US) around 20 billion dollars per year. While not a simple or quick solution, one way to begin to address the challenge of AMR and other harms from this type of farming is to focus on animal welfare as part of a One Health and Welfare approach, as better welfare requires less antibiotics usage, which may begin to break the cycle.

Keywords: animal and human welfare, industrial animal farming, antimicrobial resistance, one health and welfare, sustainable development goals

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11553 A Levinasian Perspective on the Field of Applied Ethics

Authors: Payman Tajalli, Steven Segal

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Applied ethics is an area of ethics which is looked upon most favorably as the most appropriate and useful for educational purposes; after all if ethics finds no application would any investment of time, effort and finance by the educational institutions be warranted? The current approaches to ethics in business and management often entail appealing to various types of moral theories and to this end almost every major philosophical approach has been enlisted. In this paper, we look at ethics through the philosophy of Emmanuel Levinas to argue that since ethics is ‘first philosophy’ it can neither be rule-based nor rule-governed, not something that can be worked out first and then applied to a given situation, hence the overwhelming emphasis on ‘applied ethics’ as a field of study in business and management education is unjustified. True ethics is not applied ethics. This assertion does not mean that teaching ethical theories and philosophies need to be abandoned rather it is the acceptance of the fact that an increase in cognitive awareness of such theories and ethical models and frameworks, or the mastering of techniques and procedures for ethical decision making, will not affect the desired ethical transformation in our students. Levinas himself argued for an ethics without a foundation, not one that required us to go ‘beyond good and evil’ as Nietzsche contended, rather an ethics which necessitates going ‘before good and evil'. Such an ethics does not provide us with a set of methods or techniques or a decision tree that enable us determine the rightness of an action and what we ought to do, rather it is about a way of being, an ethical posture or approach one takes in the inter-subjective relationship with the other that holds the promise of ethical conduct. Ethics in this Levinasian sense then is one of infinite and unconditional responsibility for the other person in relationship, an ethics which is not subject to negotiation, calculation or reciprocity, and as such it could neither be applied nor taught through conventional pedagogy with its focus on knowledge transfer from the teacher to student, and to this end Levinas offers a non-maieutic, non-conventional approach to pedagogy. The paper concludes that from a Levinasian perspective on ethics and education, we may need to guide our students to move away from the clear and objective professionalism of the management and applied ethics towards the murky individual spiritualism. For Levinas, this is ‘the Copernican revolution’ in ethics.

Keywords: business ethics, ethics education, Levinas, maieutic teaching, ethics without foundation

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11552 Modeling Approach for Evaluating Infiltration Rate of a Large-Scale Housing Stock

Authors: Azzam Alosaimi

Abstract:

Different countries attempt to reduce energy demands and Greenhouse Gas (GHG) emissions to mitigate global warming potential. They set different building codes to regulate excessive building’s energy losses. Energy losses occur due to pressure difference between the indoor and outdoor environments, and thus, heat transfers from one region to another. One major sources of energy loss is known as building airtightness. Building airtightness is the fundamental feature of the building envelope that directly impacts infiltration. Most of international building codes require minimum performance for new construction to ensure acceptable airtightness. The execution of airtightness required standards has become more challenging in recent years due to a lack of expertise and equipment, making it costly and time-consuming. Hence, researchers have developed predictive models to predict buildings infiltration rates to meet building codes and to reduce energy and cost. This research applies a theoretical modeling approach using Matlab software to predict mean infiltration rate distributions and total heat loss of Saudi Arabia’s housing stock.

Keywords: infiltration rate, energy demands, heating loss, cooling loss, carbon emissions

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11551 Working Title: Estimating the Power Output of Photovoltaics in Kuwait Using a Monte Carlo Approach

Authors: Mohammad Alshawaf, Rahmat Poudineh, Nawaf Alhajeri

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The power generated from photovoltaic (PV) modules is non-dispatchable on demand due to the stochastic nature of solar radiation. The random variations in the measured intensity of solar irradiance are due to clouds and, in the case of arid regions, dust storms which decrease the intensity of intensity of solar irradiance. Therefore, modeling PV power output using average, maximum, or minimum solar irradiance values is inefficient to predict power generation reliably. The overall objective of this paper is to predict the power output of PV modules using Monte Carlo approach based the weather and solar conditions measured in Kuwait. Given the 250 Wp PV module used in study, the average daily power output is 1021 Wh/day. The maximum power was generated in April and the minimum power was generated in January 1187 Wh/day and 823 Wh/day respectively. The certainty of the daily predictions varies seasonally and according to the weather conditions. The output predictions were far more certain in the summer months, for example, the 80% certainty range for August is 89 Wh/day, whereas the 80% certainty range for April is 250 Wh/day.

Keywords: Monte Carlo, solar energy, variable renewable energy, Kuwait

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