Search results for: artificial intelligence in semiconductor manufacturing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4912

Search results for: artificial intelligence in semiconductor manufacturing

2272 Transcriptional Response of Honey Bee to Differential Nutritional Status and Nosema Infection

Authors: Farida Azzouz-Olden, Arthur G. Hunt, Gloria Degrandi-Hoffman

Abstract:

Bees are confronting several environmental challenges, including the intermingled effects of malnutrition and disease. Intuitively, pollen is the healthiest nutritional choice; however, commercial substitutes, such as BeePro and MegaBee, are widely used. Herein we examined how feeding natural and artificial diets shapes transcription in the abdomen of the honey bee, and how transcription shifts in combination with Nosema parasitism. Gene ontology enrichment revealed that, compared with poor diet (carbohydrates (C)), bees fed pollen (P > C), BeePro (B > C), and MegaBee (M > C) showed a broad upregulation of metabolic processes, especially lipids; however, pollen feeding promoted more functions and superior proteolysis. The superiority of the pollen diet was also evident through the remarkable overexpression of vitellogenin in bees fed pollen instead of MegaBee or BeePro. Upregulation of bioprocesses under carbohydrates feeding compared to pollen (C > P) provided a clear poor nutritional status, uncovering stark expression changes that were slight or absent relatively to BeePro (C > B) or MegaBee (C > M). Poor diet feeding (C > P) induced starvation response genes and hippo signaling pathway, while it repressed growth through different mechanisms. Carbohydrate feeding (C > P) also elicited ‘adult behavior’, and developmental processes suggesting transition to foraging. Finally, it altered the ‘circadian rhythm’, reflecting the role of this mechanism in the adaptation to nutritional stress in mammals. Nosema-infected bees fed pollen compared to carbohydrates (PN > CN) upheld certain bioprocesses of uninfected bees (P > C). Poor nutritional status was more apparent against pollen (CN > PN) than BeePro (CN > BN) or MegaBee (CN > MN). Nosema accentuated the effects of malnutrition since more starvation-response genes and stress response mechanisms were upregulated in CN > PN compared to C > P. The bioprocess ‘Macromolecular complex assembly’ was also enriched in CN > PN, and involved genes associated with human HIV and/or influenza, thus providing potential candidates for bee-Nosema interactions. Finally, the enzyme Duox emerged as essential for guts defense in bees, similarly to Drosophila. These results provide evidence of the superior nutritional status of bees fed pollen instead of artificial substitutes in terms of overall health, even in the presence of a pathogen.

Keywords: honeybee, immunity, Nosema, nutrition, RNA-seq

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2271 Opto-Electronic Properties and Structural Phase Transition of Filled-Tetrahedral NaZnAs

Authors: R. Khenata, T. Djied, R. Ahmed, H. Baltache, S. Bin-Omran, A. Bouhemadou

Abstract:

We predict structural, phase transition as well as opto-electronic properties of the filled-tetrahedral (Nowotny-Juza) NaZnAs compound in this study. Calculations are carried out by employing the full potential (FP) linearized augmented plane wave (LAPW) plus local orbitals (lo) scheme developed within the structure of density functional theory (DFT). Exchange-correlation energy/potential (EXC/VXC) functional is treated using Perdew-Burke and Ernzerhof (PBE) parameterization for generalized gradient approximation (GGA). In addition to Trans-Blaha (TB) modified Becke-Johnson (mBJ) potential is incorporated to get better precision for optoelectronic properties. Geometry optimization is carried out to obtain the reliable results of the total energy as well as other structural parameters for each phase of NaZnAs compound. Order of the structural transitions as a function of pressure is found as: Cu2Sb type → β → α phase in our study. Our calculated electronic energy band structures for all structural phases at the level of PBE-GGA as well as mBJ potential point out; NaZnAs compound is a direct (Γ–Γ) band gap semiconductor material. However, as compared to PBE-GGA, mBJ potential approximation reproduces higher values of fundamental band gap. Regarding the optical properties, calculations of real and imaginary parts of the dielectric function, refractive index, reflectivity coefficient, absorption coefficient and energy loss-function spectra are performed over a photon energy ranging from 0.0 to 30.0 eV by polarizing incident radiation in parallel to both [100] and [001] crystalline directions.

Keywords: NaZnAs, FP-LAPW+lo, structural properties, phase transition, electronic band-structure, optical properties

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2270 In Vitro Evaluation of an Artificial Venous Valve

Authors: Joon Hock Yeo, Munirah Ismail

Abstract:

Chronic venous insufficiency is a condition where the venous wall or venous valves fail to operate properly. As such, it is difficult for the blood to return from the lower extremities back to the heart. Chronic venous insufficiency affects many people worldwide. In last decade, there have been many new and innovative designs of prosthetic venous valves to replace the malfunction native venous valves. However, thus far, to the authors’ knowledge, there is no successful prosthetic venous valve. In this project, we have developed a venous valve which could operate under low pressure. While further testing is warranted, this unique valve could potentially alleviate problems associated with chronic venous insufficiency.

Keywords: prosthetic venous valve, bi-leaflet valve, chronic venous insufficiency, valve hemodynamics

Procedia PDF Downloads 195
2269 Electronic Device Robustness against Electrostatic Discharges

Authors: Clara Oliver, Oibar Martinez

Abstract:

This paper is intended to reveal the severity of electrostatic discharge (ESD) effects in electronic and optoelectronic devices by performing sensitivity tests based on Human Body Model (HBM) standard. We explain here the HBM standard in detail together with the typical failure modes associated with electrostatic discharges. In addition, a prototype of electrostatic charge generator has been designed, fabricated, and verified to stress electronic devices, which features a compact high voltage source. This prototype is inexpensive and enables one to do a battery of pre-compliance tests aimed at detecting unexpected weaknesses to static discharges at the component level. Some tests with different devices were performed to illustrate the behavior of the proposed generator. A set of discharges was applied according to the HBM standard to commercially available bipolar transistors, complementary metal-oxide-semiconductor transistors and light emitting diodes. It is observed that high current and voltage ratings in electronic devices not necessarily provide a guarantee that the device will withstand high levels of electrostatic discharges. We have also compared the result obtained by performing the sensitivity tests based on HBM with a real discharge generated by a human. For this purpose, the charge accumulated in the person is monitored, and a direct discharge against the devices is generated by touching them. Every test has been performed under controlled relative humidity conditions. It is believed that this paper can be of interest for research teams involved in the development of electronic and optoelectronic devices which need to verify the reliability of their devices in terms of robustness to electrostatic discharges.

Keywords: human body model, electrostatic discharge, sensitivity tests, static charge monitoring

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2268 A Universal Approach to Categorize Failures in Production

Authors: Konja Knüppel, Gerrit Meyer, Peter Nyhuis

Abstract:

The increasing interconnectedness and complexity of production processes raise the susceptibility of production systems to failure. Therefore, the ability to respond quickly to failures is increasingly becoming a competitive factor. The research project "Sustainable failure management in manufacturing SMEs" is developing a methodology to identify failures in the production and select preventive and reactive measures in order to correct failures and to establish sustainable failure management systems.

Keywords: failure categorization, failure management, logistic performance, production optimization

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2267 Investigating the Impact of Knowledge Management Components on Employee Productivity

Authors: Javad Moghtader Kargaran

Abstract:

Today, attention to knowledge and management Knowledge as a strategy is very important has taken with economy becoming knowledge-oriented, how and knowing the effective management and integration of different types Knowledge (obvious-implicit) to preserve and create advantage. Competition has become very important. Knowledge is a valuable resource for empowering organizations in the direction of innovation and competition. Due to the importance of human resources in the survival of organizations, extensive efforts are made to empower them. This knowledge can lead to awareness among employees. Employees and the knowledge that is in their minds are very valuable resources for the organization, which must be managed and developed. In fact, the ultimate goal of knowledge management is to increase the intelligence and productivity of employees and the organization.

Keywords: knowledge, management, productivity, human

Procedia PDF Downloads 95
2266 Forecasting of Grape Juice Flavor by Using Support Vector Regression

Authors: Ren-Jieh Kuo, Chun-Shou Huang

Abstract:

The research of juice flavor forecasting has become more important in China. Due to the fast economic growth in China, many different kinds of juices have been introduced to the market. If a beverage company can understand their customers’ preference well, the juice can be served more attractively. Thus, this study intends to introduce the basic theory and computing process of grapes juice flavor forecasting based on support vector regression (SVR). Applying SVR, BPN and LR to forecast the flavor of grapes juice in real data, the result shows that SVR is more suitable and effective at predicting performance.

Keywords: flavor forecasting, artificial neural networks, Support Vector Regression, China

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2265 Detection of Safety Goggles on Humans in Industrial Environment Using Faster-Region Based on Convolutional Neural Network with Rotated Bounding Box

Authors: Ankit Kamboj, Shikha Talwar, Nilesh Powar

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To successfully deliver our products in the market, the employees need to be in a safe environment, especially in an industrial and manufacturing environment. The consequences of delinquency in wearing safety glasses while working in industrial plants could be high risk to employees, hence the need to develop a real-time automatic detection system which detects the persons (violators) not wearing safety glasses. In this study a convolutional neural network (CNN) algorithm called faster region based CNN (Faster RCNN) with rotated bounding box has been used for detecting safety glasses on persons; the algorithm has an advantage of detecting safety glasses with different orientation angles on the persons. The proposed method of rotational bounding boxes with a convolutional neural network first detects a person from the images, and then the method detects whether the person is wearing safety glasses or not. The video data is captured at the entrance of restricted zones of the industrial environment (manufacturing plant), which is further converted into images at 2 frames per second. In the first step, the CNN with pre-trained weights on COCO dataset is used for person detection where the detections are cropped as images. Then the safety goggles are labelled on the cropped images using the image labelling tool called roLabelImg, which is used to annotate the ground truth values of rotated objects more accurately, and the annotations obtained are further modified to depict four coordinates of the rectangular bounding box. Next, the faster RCNN with rotated bounding box is used to detect safety goggles, which is then compared with traditional bounding box faster RCNN in terms of detection accuracy (average precision), which shows the effectiveness of the proposed method for detection of rotatory objects. The deep learning benchmarking is done on a Dell workstation with a 16GB Nvidia GPU.

Keywords: CNN, deep learning, faster RCNN, roLabelImg rotated bounding box, safety goggle detection

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2264 The Effects of Circadian Rhythms Change in High Latitudes

Authors: Ekaterina Zvorykina

Abstract:

Nowadays, Arctic and Antarctic regions are distinguished to be one of the most important strategic resources for global development. Nonetheless, living conditions in Arctic regions still demand certain improvements. As soon as the region is rarely populated, one of the main points of interest is health accommodation of the people, who migrate to Arctic region for permanent and shift work. At Arctic and Antarctic latitudes, personnel face polar day and polar night conditions during the time of the year. It means that they are deprived of natural sunlight in winter season and have continuous daylight in summer. Firstly, the change in light intensity during 24-hours period due to migration affects circadian rhythms. Moreover, the controlled artificial light in winter is also an issue. The results of the recent studies on night shift medical professionals, who were exposed to permanent artificial light, have already demonstrated higher risks in cancer, depression, Alzheimer disease. Moreover, people exposed to frequent time zones change are also subjected to higher risks of heart attack and cancer. Thus, our main goals are to understand how high latitude work and living conditions can affect human health and how it can be prevented. In our study, we analyze molecular and cellular factors, which play important role in circadian rhythm change and distinguish main risk groups in people, migrating to high latitudes. The main well-studied index of circadian timing is melatonin or its metabolite 6-sulfatoxymelatonin. In low light intensity melatonin synthesis is disturbed and as a result human organism requires more time for sleep, which is still disregarded when it comes to working time organization. Lack of melatonin also causes shortage in serotonin production, which leads to higher depression risk. Melatonin is also known to inhibit oncogenes and increase apoptosis level in cells, the main factors for tumor growth, as well as circadian clock genes (for example Per2). Thus, people who work in high latitudes can be distinguished as a risk group for cancer diseases and demand more attention. Clock/Clock genes, known to be one of the main circadian clock regulators, decrease sensitivity of hypothalamus to estrogen and decrease glucose sensibility, which leads to premature aging and oestrous cycle disruption. Permanent light exposure also leads to accumulation superoxide dismutase and oxidative stress, which is one of the main factors for early dementia and Alzheimer disease. We propose a new screening system adjusted for people, migrating from middle to high latitudes and accommodation therapy. Screening is focused on melatonin and estrogen levels, sleep deprivation and neural disorders, depression level, cancer risks and heart and vascular disorders. Accommodation therapy includes different types artificial light exposure, additional melatonin and neuroprotectors. Preventive procedures can lead to increase of migration intensity to high latitudes and, as a result, the prosperity of Arctic region.

Keywords: circadian rhythm, high latitudes, melatonin, neuroprotectors

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2263 Smart Services for Easy and Retrofittable Machine Data Collection

Authors: Till Gramberg, Erwin Gross, Christoph Birenbaum

Abstract:

This paper presents the approach of the Easy2IoT research project. Easy2IoT aims to enable companies in the prefabrication sheet metal and sheet metal processing industry to enter the Industrial Internet of Things (IIoT) with a low-threshold and cost-effective approach. It focuses on the development of physical hardware and software to easily capture machine activities from on a sawing machine, benefiting various stakeholders in the SME value chain, including machine operators, tool manufacturers and service providers. The methodological approach of Easy2IoT includes an in-depth requirements analysis and customer interviews with stakeholders along the value chain. Based on these insights, actions, requirements and potential solutions for smart services are derived. The focus is on providing actionable recommendations, competencies and easy integration through no-/low-code applications to facilitate implementation and connectivity within production networks. At the core of the project is a novel, non-invasive measurement and analysis system that can be easily deployed and made IIoT-ready. This system collects machine data without interfering with the machines themselves. It does this by non-invasively measuring the tension on a sawing machine. The collected data is then connected and analyzed using artificial intelligence (AI) to provide smart services through a platform-based application. Three Smart Services are being developed within Easy2IoT to provide immediate benefits to users: Wear part and product material condition monitoring and predictive maintenance for sawing processes. The non-invasive measurement system enables the monitoring of tool wear, such as saw blades, and the quality of consumables and materials. Service providers and machine operators can use this data to optimize maintenance and reduce downtime and material waste. Optimize Overall Equipment Effectiveness (OEE) by monitoring machine activity. The non-invasive system tracks machining times, setup times and downtime to identify opportunities for OEE improvement and reduce unplanned machine downtime. Estimate CO2 emissions for connected machines. CO2 emissions are calculated for the entire life of the machine and for individual production steps based on captured power consumption data. This information supports energy management and product development decisions. The key to Easy2IoT is its modular and easy-to-use design. The non-invasive measurement system is universally applicable and does not require specialized knowledge to install. The platform application allows easy integration of various smart services and provides a self-service portal for activation and management. Innovative business models will also be developed to promote the sustainable use of the collected machine activity data. The project addresses the digitalization gap between large enterprises and SME. Easy2IoT provides SME with a concrete toolkit for IIoT adoption, facilitating the digital transformation of smaller companies, e.g. through retrofitting of existing machines.

Keywords: smart services, IIoT, IIoT-platform, industrie 4.0, big data

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2262 Mastering Digital Transformation with the Strategy Tandem Innovation Inside-Out/Outside-In: An Approach to Drive New Business Models, Services and Products in the Digital Age

Authors: S. N. Susenburger, D. Boecker

Abstract:

In the age of Volatility, Uncertainty, Complexity, and Ambiguity (VUCA), where digital transformation is challenging long standing traditional hardware and manufacturing companies, innovation needs a different methodology, strategy, mindset, and culture. What used to be a mindset of scaling per quantity is now shifting to orchestrating ecosystems, platform business models and service bundles. While large corporations are trying to mimic the nimbleness and versatile mindset of startups in the core of their digital strategies, they’re at the frontier of facing one of the largest organizational and cultural changes in history. This paper elaborates on how a manufacturing giant transformed its Corporate Information Technology (IT) to enable digital and Internet of Things (IoT) business while establishing the mindset and the approaches of the Innovation Inside-Out/Outside-In Strategy. It gives insights into the core elements of an innovation culture and the tactics and methodologies leveraged to support the cultural shift and transformation into an IoT company. This paper also outlines the core elements for an innovation culture and how the persona 'Connected Engineer' thrives in the digital innovation environment. Further, it explores how tapping domain-focused ecosystems in vibrant innovative cities can be used as a part of the strategy to facilitate partner co-innovation. Therefore, findings from several use cases, observations and surveys led to conclusion for the strategy tandem of Innovation Inside-Out/Outside-In. The findings indicate that it's crucial in which phases and maturity level the Innovation Inside-Out/Outside-In Strategy is activated: cultural aspects of the business and the regional ecosystem need to be considered, as well as cultural readiness from management and active contributors. The 'not invented here syndrome' is a barrier of large corporations that need to be addressed and managed to successfully drive partnerships, as well as embracing co-innovation and a mindset shifting away from physical products toward new business models, services, and IoT platforms. This paper elaborates on various methodologies and approaches tested in different countries and cultures, including the U.S., Brazil, Mexico, and Germany.

Keywords: innovation management, innovation culture, innovation methodologies, digital transformation

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2261 Classical Music Unplugged: The Future of Classical Music Performance: Tradition, Technology, and Audience Engagement

Authors: Orit Wolf

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Classical music performance is undergoing a profound transformation, marked by a confluence of technological advancements and evolving cultural dynamics. This academic paper explores the multifaceted changes and challenges faced by classical music performance, considering the impact of artificial intelligence (AI) along with other vital factors shaping this evolution. In the contemporary era, classical music is experiencing shifts in performance practices. This paper delves into these changes, emphasizing the need for adaptability within the classical music world. From repertoire selection and concert formats to artistic expression, performers and institutions navigate a delicate balance between tradition and innovation. We explore how these changes impact the authenticity and vitality of classical music performances. Furthermore, the influence of AI in the classical music concert world cannot be underestimated. AI technologies are making inroads into various aspects, from composition assistance to rehearsal and live performances. This paper examines the transformative effects of AI, considering how it enhances precision, adaptability, and creative exploration for musicians. We explore the implications for composers, performers, and the overall concert experience while addressing ethical concerns and creative opportunities. In addition to AI, there is the importance of cross-genre interactions within the classical music sphere. Mash-ups and collaborations with artists from diverse musical backgrounds are redefining the boundaries of classical music and creating works that resonate with a wider and more diverse audience. The benefits of cross-pollination in classical music seem crucial, offering a fresh perspective to listeners. As an active concert artist, Orit Wolf will share how the expectations of classical music audiences are evolving. Modern concertgoers seek not only exceptional musical performances but also immersive experiences that may involve technology, multimedia, and interactive elements. This paper examines how classical musicians and institutions are adapting to these changing expectations, using technology and innovative concert formats to deliver a unique and enriched experience to their audiences. As these changes and challenges reshape the classical music world, the need for a harmonious coexistence of tradition, technology, and innovation becomes evident. Musicians, composers, and institutions are striving to find a balance that ensures classical music remains relevant in a rapidly changing cultural landscape while maintaining the value it brings to compositions and audiences. This paper, therefore, aims to explore the evolving trends in classical music performance. It considers the influence of AI as one element within the broader context of change, highlighting the necessity of adaptability, cross-genre interactions, and a response to evolving audience expectations. By doing so, the classical music world can navigate this transformative period while preserving its timeless traditions and adding value to both performers and listeners. Orit Wolf, an international concert pianist, fulfils her vision to bring this music in new ways to mass audiences and will share her personal and professional experience as an artist who goes on stage and makes disruptive concerts.

Keywords: cross culture collaboration, music performance and ai, classical music in the digital age, classical concerts, innovation and technology, performance innovation, audience engagement in classical concerts

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2260 Seek First to Regulate, Then to Understand: The Case for Preemptive Regulation of Robots

Authors: Catherine McWhorter

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Robotics is a fast-evolving field lacking comprehensive and harm-mitigating regulation; it also lacks critical data on how human-robot interaction (HRI) may affect human psychology. As most anthropomorphic robots are intended as substitutes for humans, this paper asserts that the commercial robotics industry should be preemptively regulated at the federal level such that robots capable of embodying a victim role in criminal scenarios (“vicbots”) are prohibited until clinical studies determine their effects on the user and society. The results of these studies should then inform more permanent legislation that strives to mitigate risks of harm without infringing upon fundamental rights or stifling innovation. This paper explores these concepts through the lens of the sex robot industry. The sexbot industry offers some of the most realistic, interactive, and customizable robots for sale today. From approximately 2010 until 2017, some sex robot producers, such as True Companion, actively promoted ‘vicbot’ culture with personalities like “Frigid Farrah” and “Young Yoko” but received significant public backlash for fetishizing rape and pedophilia. Today, “Frigid Farrah” and “Young Yoko” appear to have vanished. Sexbot producers have replaced preprogrammed vicbot personalities in favor of one generic, customizable personality. According to the manufacturer ainidoll.com, when asked, there is only one thing the user won’t be able to program the sexbot to do – “…give you drama”. The ability to customize vicbot personas is possible with today’s generic personality sexbots and may undermine the intent of some current legislative efforts. Current debate on the effects of vicbots indicates a lack of consensus. Some scholars suggest vicbots may reduce the rate of actual sex crimes, and some suggest that vicbots will, in fact, create sex criminals, while others cite their potential for rehabilitation. Vicbots may have value in some instances when prescribed by medical professionals, but the overall uncertainty and lack of data further underscore the need for preemptive regulation and clinical research. Existing literature on exposure to media violence and its effects on prosocial behavior, human aggression, and addiction may serve as launch points for specific studies into the hyperrealism of vicbots. Of course, the customization, anthropomorphism and artificial intelligence of sexbots, and therefore more mainstream robots, will continue to evolve. The existing sexbot industry offers an opportunity to preemptively regulate and to research answers to these and many more questions before this type of technology becomes even more advanced and mainstream. Robots pose complicated moral, ethical, and legal challenges, most of which are beyond the scope of this paper. By examining the possibility for custom vicbots via the sexbots industry, reviewing existing literature on regulation, media violence, and vicbot user effects, this paper strives to underscore the need for preemptive federal regulation prohibiting vicbot capabilities in robots while advocating for further research into the potential for the user and societal harm by the same.

Keywords: human-robot interaction effects, regulation, research, robots

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2259 An Artificial Neural Network Model Based Study of Seismic Wave

Authors: Hemant Kumar, Nilendu Das

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A study based on ANN structure gives us the information to predict the size of the future in realizing a past event. ANN, IMD (Indian meteorological department) data and remote sensing were used to enable a number of parameters for calculating the size that may occur in the future. A threshold selected specifically above the high-frequency harvest reached the area during the selected seismic activity. In the field of human and local biodiversity it remains to obtain the right parameter compared to the frequency of impact. But during the study the assumption is that predicting seismic activity is a difficult process, not because of the parameters involved here, which can be analyzed and funded in research activity.

Keywords: ANN, Bayesion class, earthquakes, IMD

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2258 A Sustainable Supplier Selection and Order Allocation Based on Manufacturing Processes and Product Tolerances: A Multi-Criteria Decision Making and Multi-Objective Optimization Approach

Authors: Ravi Patel, Krishna K. Krishnan

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In global supply chains, appropriate and sustainable suppliers play a vital role in supply chain development and feasibility. In a larger organization with huge number of suppliers, it is necessary to divide suppliers based on their past history of quality and delivery of each product category. Since performance of any organization widely depends on their suppliers, well evaluated selection criteria and decision-making models lead to improved supplier assessment and development. In this paper, SCOR® performance evaluation approach and ISO standards are used to determine selection criteria for better utilization of supplier assessment by using hybrid model of Analytic Hierchchy Problem (AHP) and Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (FTOPSIS). AHP is used to determine the global weightage of criteria which helps TOPSIS to get supplier score by using triangular fuzzy set theory. Both qualitative and quantitative criteria are taken into consideration for the proposed model. In addition, a multi-product and multi-time period model is selected for order allocation. The optimization model integrates multi-objective integer linear programming (MOILP) for order allocation and a hybrid approach for supplier selection. The proposed MOILP model optimizes order allocation based on manufacturing process and product tolerances as per manufacturer’s requirement for quality product. The integrated model and solution approach are tested to find optimized solutions for different scenario. The detailed analysis shows the superiority of proposed model over other solutions which considered individual decision making models.

Keywords: AHP, fuzzy set theory, multi-criteria decision making, multi-objective integer linear programming, TOPSIS

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2257 Quality Culture Framework Proposal for Libyan Industrial Companies

Authors: Mostafa Ahmed Shokshok

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Libyan industrial companies face many challenges in today's competitive market. Quality management culture approaches is one of these challenges which may furnish the road to the Libyan industrial companies to effectively empower their employees and improve their ability to respond to the international competition. The primary objective of this paper is to design a practical approach to guide Libyan industrial companies toward successful quality culture implementation.

Keywords: TQM, quality culture, Libyan manufacturing industries, quality framework

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2256 Deep Learning-Based Classification of 3D CT Scans with Real Clinical Data; Impact of Image format

Authors: Maryam Fallahpoor, Biswajeet Pradhan

Abstract:

Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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2255 White Light Emitting Carbon Dots- Surface Modification of Carbon Dots Using Auxochromes

Authors: Manasa Perikala, Asha Bhardwaj

Abstract:

Fluorescent carbon dots (CDs), a young member of Carbon nanomaterial family, has gained a lot of research attention across the globe due to its highly luminescent emission properties, non-toxic behavior, stable emission properties, and zero re-absorption lose. These dots have the potential to replace the use of traditional semiconductor quantum dots in light-emitting devices (LED’s, fiber lasers) and other photonic devices (temperature sensor, UV detector). However, One major drawback of Carbon dots is that, till date, the actual mechanism of photoluminescence (PL) in carbon dots is still an open topic of discussion among various researchers across the globe. PL mechanism of CDs based on wide particle size distribution, the effect of surface groups, hybridization in carbon, and charge transfer mechanisms have been proposed. Although these mechanisms explain PL of CDs to an extent, no universally accepted mechanism to explain complete PL behavior of these dots is put forth. In our work, we report parameters affecting the size and surface of CDs, such as time of the reaction, synthesis temperature and concentration of precursors and their effects on the optical properties of the carbon dots. The effect of auxochromes on the emission properties and re-modification of carbon surface using an external surface functionalizing agent is discussed in detail. All the explanations have been supported by UV-Visible absorption, emission spectroscopies, Fourier transform infrared spectroscopy and Transmission electron microscopy and X-Ray diffraction techniques. Once the origin of PL in CDs is understood, parameters affecting PL centers can be modified to tailor the optical properties of these dots, which can enhance their applications in the fabrication of LED’s and other photonic devices out of these carbon dots.

Keywords: carbon dots, photoluminescence, size effects on emission in CDs, surface modification of carbon dots

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2254 Implementing Quality Function Deployment Tool for a Customer Driven New Product Development in a Kuwait SME

Authors: Asma AlQahtani, Jumana AlHadad, Maryam AlQallaf, Shoug AlHasan

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New product development (NPD) is the complete process of bringing a new product to the customer by integrating the two broad divisions; one involving the idea generation, product design and detail engineering; and the other involving market research and marketing analysis. It is a common practice for companies to undertake some of these tasks simultaneously (concurrent engineering) and also consider them as an ongoing process (continuous development). The current study explores the framework and methodology for a new product development process utilizing the Quality Function Deployment (QFD) tool for bringing the customer opinion into the product development process. An elaborate customer survey with focus groups in the region was carried out to ensure that customer requirements are integrated into new products as early as the design stage including identifying the recognition of need for the new product. A QFD Matrix (House of Quality) was prepared that links customer requirements to product engineering requirements and a feasibility study and risk assessment exercise was carried out for a Small and Medium Enterprise (SME) in Kuwait for development of the new product. SMEs in Kuwait, particularly in manufacturing sector are mainly focused on serving the local demand, and often lack of product quality adversely affects the ability of the companies to compete on a regional/global basis. Further, lack of focus on identifying customer requirements often deters SMEs to envisage the idea of a New Product Development. The current study therefore focuses in utilizing QFD Matrix right from the conceptual design to detail design and to some extent, extending the link this to design of the manufacturing system. The outcome of the project resulted in a development of the prototype for a new molded product which can ensure consistency between the customer’s requirements and the measurable characteristics of the product. The Engineering Economics and Cost studies were also undertaken to analyse the viability of the new product, the results of which was also linked to the successful implementation of the initial QFD Matrix.

Keywords: Quality Function Deployment, QFD Matrix, new product development, NPD, Kuwait SMEs, prototype development

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2253 Photo-Degradation Black 19 Dye with Synthesized Nano-Sized ZnS

Authors: M. Tabatabaee, R. Mohebat, M. Baranian

Abstract:

Textile industries produce large volumes of colored dye effluents which are toxic and non-biodegradable. Earlier studies have shown that a wide range of organic substrates can be completely photo mineralized in the presence of photocatalysts and oxidant agents. ZnO and TiO2 are important photocatalysts with high catalytic activity that have attracted much research attention. Zinc sulfide is one of the semiconductor nanomaterials that can be used for the production of optical sensitizers, photocatalysts, electroluminescent materials, optical sensors and for solar energy conversion. The synthesis of ZnS nanoparticles has been tried by various methods and sulfide sources. Elementary sulfur powder, H2S or Na2S are used as sulfide sources for synthesis of ZnS nano particles. Recently, solar energy is has been successfully used for photocatalytic degradation of dye pollutant. Studies have shown that the use of metal oxides or sulfides with ZnO or TiO2 can significantly enhance the photocatalytic activity of them. In this research, Nano-sized zinc sulfide was synthesized successfully by a simple method using thioasetamide as sulfide source in the presence of polyethylene glycol (PEG 2000). X-ray diffraction (XRD) spectroscopy scanning electron microscope (SEM) was used to characterize the structure and morphology synthesized powder. The effect of photocatalytic activity of prepared ZnS and ZnS/ZnO, on degradation of direct Black19 under UV and sunlight irradiation was investigated. The effects of various parameters such as amount of photocatalyst, pH, initial dye concentration and irradiation time on decolorization rate were systematically investigated. Results show that more than 80% of 500 mgL-1 of dye decolorized in 60-min reaction time under UV and solar irradiation in the presence of ZnS nanoparticles. Whereas, mixed ZnS/ZnO (50%) can decolorize more than 80% of dye in the same conditions.

Keywords: zinc sulfide, nano articles, photodegradation, solar light

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2252 The Effect of Leadership Styles on Continuous Improvement Teams

Authors: Paul W. Murray

Abstract:

This research explores the relationship between leadership style and continuous improvement (CI) teams. CI teams have several features that are not always found in other types of teams, including multi-functional members, short time period for performance, positive and actionable results, and exposure to senior leadership. There is not only one best style of leadership for these teams. Instead, it is important to select the best leadership style for the situation. The leader must have the flexibility to change styles and the skill to use the chosen style effectively in order to ensure the team’s success.

Keywords: leadership style, lean manufacturing, teams, cross-functional

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2251 Photoelectrochemical Water Splitting from Earth-Abundant CuO Thin Film Photocathode: Enhancing Performance and Photo-Stability through Deposition of Overlayers

Authors: Wilman Septina, Rajiv R. Prabhakar, Thomas Moehl, David Tilley

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Cupric oxide (CuO) is a promising absorber material for the fabrication of scalable, low cost solar energy conversion devices, due to the high abundance and low toxicity of copper. It is a p-type semiconductor with a band gap of around 1.5 eV, absorbing a significant portion of the solar spectrum. One of the main challenges in using CuO as solar absorber in an aqueous system is its tendency towards photocorrosion, generating Cu2O and metallic Cu. Although there have been several reports of CuO as a photocathode for hydrogen production, it is unclear how much of the observed current actually corresponds to H2 evolution, as the inevitability of photocorrosion is usually not addressed. In this research, we investigated the effect of the deposition of overlayers onto CuO thin films for the purpose of enhancing its photostability as well as performance for water splitting applications. CuO thin film was fabricated by galvanic electrodeposition of metallic copper onto gold-coated FTO substrates, followed by annealing in air at 600 °C. Photoelectrochemical measurement of the bare CuO film using 1 M phosphate buffer (pH 6.9) under simulated AM 1.5 sunlight showed a current density of ca. 1.5 mA cm-2 (at 0.4 VRHE), which photocorroded to Cu metal upon prolonged illumination. This photocorrosion could be suppressed by deposition of 50 nm-thick TiO2, deposited by atomic layer deposition. In addition, we found that insertion of an n-type CdS layer, deposited by chemical bath deposition, between the CuO and TiO2 layers was able to enhance significantly the photocurrent compared to without the CdS layer. A photocurrent of over 2 mA cm-2 (at 0 VRHE) was observed using the photocathode stack FTO/Au/CuO/CdS/TiO2/Pt. Structural, electrochemical, and photostability characterizations of the photocathode as well as results on various overlayers will be presented.

Keywords: CuO, hydrogen, photoelectrochemical, photostability, water splitting

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2250 Chaotic Electronic System with Lambda Diode

Authors: George Mahalu

Abstract:

The Chua diode has been configured over time in various ways, using electronic structures like as operational amplifiers (OAs) or devices with gas or semiconductors. When discussing the use of semiconductor devices, tunnel diodes (Esaki diodes) are most often considered, and more recently, transistorized configurations such as lambda diodes. The paper-work proposed here uses in the modeling a lambda diode type configuration consisting of two Junction Field Effect Transistors (JFET). The original scheme is created in the MULTISIM electronic simulation environment and is analyzed in order to identify the conditions for the appearance of evolutionary unpredictability specific to nonlinear dynamic systems with chaos-induced behavior. The chaotic deterministic oscillator is one autonomous type, a fact that places it in the class of Chua’s type oscillators, the only significant and most important difference being the presence of a nonlinear device like the one mentioned structure above. The chaotic behavior is identified both by means of strange attractor-type trajectories and visible during the simulation and by highlighting the hypersensitivity of the system to small variations of one of the input parameters. The results obtained through simulation and the conclusions drawn are useful in the further research of ways to implement such constructive electronic solutions in theoretical and practical applications related to modern small signal amplification structures, to systems for encoding and decoding messages through various modern ways of communication, as well as new structures that can be imagined both in modern neural networks and in those for the physical implementation of some requirements imposed by current research with the aim of obtaining practically usable solutions in quantum computing and quantum computers.

Keywords: chaos, lambda diode, strange attractor, nonlinear system

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2249 The Role of Middle Managers SBU's in Context of Change: Sense-Making Approach

Authors: Hala Alioua, Alberic Tellier

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This paper is designed to spotlight the research on corporate strategic planning, by emphasizing the role of middle manager of SBU’s and related issues such as the context of vision change. Previous research on strategic vision has been focused principally at the SME, with relatively limited consideration given to the role of middle managers SBU’s in the context of change. This project of research has been done by using a single case study. We formulated through our immersion for 2.5 years on the ground and by a qualitative method and abduction approach. This entity that we analyze is a subsidiary of multinational companies headquartered in Germany, specialized in manufacturing automotive equipment. The "Delta Company" is a French manufacturing plant that has undergone numerous changes over the past three years. The two major strategic changes that have a significant impact on the Delta plant are the strengths of its core business through « lead plant strategy» in 2011 and the implementation of a new strategic vision in 2014. These consecutive changes impact the purpose of the mission of the middle managers. The plant managers ask the following questions: How the middle managers make sense of the corporate strategic planning imposed by the parent company? How they appropriate the new vision and decline it into actions on the ground? We chose the individual interview technique through open-ended questions as the source of data collection. We first of all carried out an exploratory approach by interviewing 8 members of the Management committee’s decision and 19 heads of services. The first findings and results show that exist a divergence of opinion and interpretations of the corporate strategic planning among organization members and there are difficulties to make sense and interpretations of the signals of the environment. The lead plant strategy enables new projects which insure the workload of Delta Company. Nevertheless, it creates a tension and stress among the middle managers because its provoke lack of resources to the detriment of their main jobs as manufacturer plant. The middle managers does not have a clear vision and they are wondering if the new strategic vision means more autonomy and less support from the group.

Keywords: change, middle managers, vision, sensemaking

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2248 Digestion Optimization Algorithm: A Novel Bio-Inspired Intelligence for Global Optimization Problems

Authors: Akintayo E. Akinsunmade

Abstract:

The digestion optimization algorithm is a novel biological-inspired metaheuristic method for solving complex optimization problems. The algorithm development was inspired by studying the human digestive system. The algorithm mimics the process of food ingestion, breakdown, absorption, and elimination to effectively and efficiently search for optimal solutions. This algorithm was tested for optimal solutions on seven different types of optimization benchmark functions. The algorithm produced optimal solutions with standard errors, which were compared with the exact solution of the test functions.

Keywords: bio-inspired algorithm, benchmark optimization functions, digestive system in human, algorithm development

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2247 Peculiarities of Internal Friction and Shear Modulus in 60Co γ-Rays Irradiated Monocrystalline SiGe Alloys

Authors: I. Kurashvili, G. Darsavelidze, T. Kimeridze, G. Chubinidze, I. Tabatadze

Abstract:

At present, a number of modern semiconductor devices based on SiGe alloys have been created in which the latest achievements of high technologies are used. These devices might cause significant changes to networking, computing, and space technology. In the nearest future new materials based on SiGe will be able to restrict the A3B5 and Si technologies and firmly establish themselves in medium frequency electronics. Effective realization of these prospects requires the solution of prediction and controlling of structural state and dynamical physical –mechanical properties of new SiGe materials. Based on these circumstances, a complex investigation of structural defects and structural-sensitive dynamic mechanical characteristics of SiGe alloys under different external impacts (deformation, radiation, thermal cycling) acquires great importance. Internal friction (IF) and shear modulus temperature and amplitude dependences of the monocrystalline boron-doped Si1-xGex(x≤0.05) alloys grown by Czochralski technique is studied in initial and 60Co gamma-irradiated states. In the initial samples, a set of dislocation origin relaxation processes and accompanying modulus defects are revealed in a temperature interval of 400-800 ⁰C. It is shown that after gamma-irradiation intensity of relaxation internal friction in the vicinity of 280 ⁰C increases and simultaneously activation parameters of high temperature relaxation processes reveal clear rising. It is proposed that these changes of dynamical mechanical characteristics might be caused by a decrease of the dislocation mobility in the Cottrell atmosphere enriched by the radiation defects.

Keywords: internal friction, shear modulus, gamma-irradiation, SiGe alloys

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2246 Measurement Technologies for Advanced Characterization of Magnetic Materials Used in Electric Drives and Automotive Applications

Authors: Lukasz Mierczak, Patrick Denke, Piotr Klimczyk, Stefan Siebert

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Due to the high complexity of the magnetization in electrical machines and influence of the manufacturing processes on the magnetic properties of their components, the assessment and prediction of hysteresis and eddy current losses has remained a challenge. In the design process of electric motors and generators, the power losses of stators and rotors are calculated based on the material supplier’s data from standard magnetic measurements. This type of data does not include the additional loss from non-sinusoidal multi-harmonic motor excitation nor the detrimental effects of residual stress remaining in the motor laminations after manufacturing processes, such as punching, housing shrink fitting and winding. Moreover, in production, considerable attention is given to the measurements of mechanical dimensions of stator and rotor cores, whereas verification of their magnetic properties is typically neglected, which can lead to inconsistent efficiency of assembled motors. Therefore, to enable a comprehensive characterization of motor materials and components, Brockhaus Measurements developed a range of in-line and offline measurement technologies for testing their magnetic properties under actual motor operating conditions. Multiple sets of experimental data were obtained to evaluate the influence of various factors, such as elevated temperature, applied and residual stress, and arbitrary magnetization on the magnetic properties of different grades of non-oriented steel. Measured power loss for tested samples and stator cores varied significantly, by more than 100%, comparing to standard measurement conditions. Quantitative effects of each of the applied measurement were analyzed. This research and applied Brockhaus measurement methodologies emphasized the requirement for advanced characterization of magnetic materials used in electric drives and automotive applications.

Keywords: magnetic materials, measurement technologies, permanent magnets, stator and rotor cores

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2245 Role of Chloride Ions on The Properties of Electrodeposited ZnO Nanostructures

Authors: L. Mentar, O. Baka, M. R. Khelladi, A. Azizi

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Zinc oxide (ZnO), as a transparent semiconductor with a wide band gap of 3.4 eV and a large exciton binding energy of 60 meV at room temperature, is one of the most promising materials for a wide range of modern applications. With the development of film growth technologies and intense recent interest in nanotechnology, several varieties of ZnO nanostructured materials have been synthesized almost exclusively by thermal evaporation methods, particularly chemical vapor deposition (CVD), which generally require a high growth temperature above 550 °C. In contrast, wet chemistry techniques such as hydrothermal synthesis and electro-deposition are promising alternatives to synthesize ZnO nanostructures, especially at a significantly lower temperature (below 200°C). In this study, the electro-deposition method was used to produce zinc oxide (ZnO) nanostructures on fluorine-doped tin oxide (FTO)-coated conducting glass substrate from chloride bath. We present the influence of KCl concentrations on the electro-deposition process, morphological, structural and optical properties of ZnO nanostructures. The potentials of electro-deposition of ZnO were determined using the cyclic voltammetry. From the Mott-Schottky measurements, the flat-band potential and the donor density for the ZnO nanostructure are determined. Field emission scanning electron microscopy (FESEM) images showed different sizes and morphologies of the nanostructures which depends on the concentrations of Cl-. Very netted hexagonal grains are observed for the nanostructures deposited at 0.1M of KCl. X-ray diffraction (XRD) study confirms the Wurtzite phase of the ZnO nanostructures with a preferred oriented along (002) plane normal to the substrate surface. UV-Visible spectra showed a significant optical transmission (~80%), which decreased with low Cl-1 concentrations. The energy band gap values have been estimated to be between 3.52 and 3.80 eV.

Keywords: Cl-, electro-deposition, FESEM, Mott-Schottky, XRD, ZnO

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2244 Effect of Al on Glancing Angle Deposition Synthesized In₂O₃ Nanocolumn for Photodetector Application

Authors: Chitralekha Ngangbam, Aniruddha Mondal, Naorem Khelchand Singh

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Aluminium (Al) doped In2O3 (Indium Oxide) nanocolumn array was synthesized by glancing angle deposition (GLAD) technique on Si (n-type) substrate for photodetector application. The sample was characterized by scanning electron microscopy (SEM). The average diameter of the nanocolumn was calculated from the top view of the SEM image and found to be ∼80 nm. The length of the nanocolumn (~500 nm) was calculated from cross sectional SEM image and it shows that the nanocolumns are perpendicular to the substrate. The EDX analysis confirmed the presence of Al (Aluminium), In (Indium), O (Oxygen) elements in the samples. The XRD patterns of the Al-doped In2O3 nanocolumn show the presence of different phases of the Al doped In2O3 nanocolumn i.e. (222) and (622). Three different peaks were observed from the PL analysis of Al doped In2O3 nanocolumn at 365 nm, 415 nm and 435 nm respectively. The peak at PL emission at 365 nm can be attributed to the near band gap transition of In2O3 whereas the peaks at 415 nm and 435 nm can be attributed to the trap state emissions due to oxygen vacancies and oxygen–indium vacancy centre in Al doped In2O3 nanocolumn. The current-voltage (I–V) characteristics of the Al doped In2O3 nanocolumn based detector was measured through the Au Schottky contact. The devices were then examined under the halogen light (20 W) illumination for photocurrent measurement. The Al-doped In2O3 nanocolumn based optical detector showed high conductivity and low turn on voltage at 0.69 V under white light illumination. A maximum photoresponsivity of 82 A/W at 380 nm was observed for the device. The device shows a high internal gain of ~267 at UV region (380 nm) and ∼127 at visible region (760 nm). Also the rise time and fall time for the device at 650 nm is 0.15 and 0.16 sec respectively which makes it suitable for fast response detector.

Keywords: glancing angle deposition, nanocolumn, semiconductor, photodetector, indium oxide

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2243 Optical Breather in Phosphorene Monolayer

Authors: Guram Adamashvili

Abstract:

Surface plasmon polariton is a surface optical wave which undergoes a strong enhancement and spatial confinement of its wave amplitude near an interface of two-dimensional layered structures. Phosphorene (single-layer black phosphorus) and other two-dimensional anisotropic phosphorene-like materials are recognized as promising materials for potential future applications of surface plasmon polariton. A theory of an optical breather of self-induced transparency for surface plasmon polariton propagating in monolayer or few-layer phosphorene is developed. A theory of an optical soliton of self-induced transparency for surface plasmon polariton propagating in monolayer or few-layer phosphorene have been investigated earlier Starting from the optical nonlinear wave equation for surface TM-modes interacting with a two-dimensional layer of atomic systems or semiconductor quantum dots and a phosphorene monolayer (or other two-dimensional anisotropic material), we have obtained the evolution equations for the electric field of the breather. In this case, one finds that the evolution of these pulses become described by the damped Bloch-Maxwell equations. For surface plasmon polariton fields, breathers are found to occur. Explicit relations of the dependence of breathers on the local media, phosphorene anisotropic conductivity, transition layer properties and transverse structures of the SPP, are obtained and will be given. It is shown that the phosphorene conductivity reduces exponentially the amplitude of the surface breather of SIT in the process of propagation. The direction of propagation corresponding to the maximum and minimum damping of the amplitude are assigned along the armchair and zigzag directions of black phosphorus nano-film, respectively. The most rapid damping of the intensity occurs when the polarization of breather is along the armchair direction.

Keywords: breathers, nonlinear waves, solitons, surface plasmon polaritons

Procedia PDF Downloads 149