Taif c.v. english
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Taif Al Jorani is seeking a position that utilizes his technical and managerial skills as an architect. He has over 10 years of experience in Iraq working on housing projects, infrastructure design, and commercial building projects. He holds a Bachelor's degree in Architecture from the University of Technology in Baghdad. He is a certified Building Analyst Professional and is skilled in AutoCAD, 3DsMax, Revit, and Microsoft Office.
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the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
官方认证美国密歇根州立大学毕业证学位证书原版一模一样
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本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma
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2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
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8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
Embedded machine learning-based road conditions and driving behavior monitoring
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Understanding Inductive Bias in Machine Learning
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Recycled Concrete Aggregate in Construction Part II
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Casting-Defect-inSlab continuous casting.pdf
Casting-Defect-inSlab continuous casting. Casting-Defect-inSlab continuous casting. Casting-Defect-inSlab continuous casting. Casting-Defect-inSlab continuous casting. Casting-Defect-inSlab continuous casting. Casting-Defect-inSlab continuous casting. Casting-Defect-inSlab continuous casting. Casting-Defect-inSlab continuous casting
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
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Recycled Concrete Aggregate in Construction Part III
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMS
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
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Taif c.v. english
- 1. Taif A Jorani 9614 Labette Drive - Saint Louis, MO 63123 , USA Tel : 001 ( 3142430672 ) Email : taif_aljorani@yahoo.com Tel : 00964 7711380372 Email : Aljorani_taif@yahoo.com _____________________________________________________________________________ _ Objective: To work with a firm where my technical and managerial skills can be effectively utilized and further enhanced. Personal I am an American citizen of middle- eastern origin . I was born and raised in Iraq, Profile: where I finished my bi-lingual university studies in Architecture. Education: Bachelor of Architecture University of Technology Sept. 1994 – June. 2001 Baghdad, Iraq Experience: July. 2002 – Mar. 2003 The Ministry of Housing and Construction Baghdad , Iraq Title: Architect • Design and construction supervision of miscellaneous housing projects. • Infrastructure and civil facilities management. • Architectural mapping using AutoCAD and 3D Max. Experience: Mar. 2004 – Aug. 2005 Al-Idrisi & Associates Architects, Inc. Baghdad, Iraq Title: Architect • Schematic design for buildings and all their aspects. • Urban planning, landscape architecture and site development. • Cost estimation and project management. • Construction site supervision and inspection. Experience: Sept. 2005 – July. 2006 Al Rrukn Almuemari Bureau Al Mansour Bureau • I assisted in the design of Arsat Hindia a large commercial building in Baghdad. The building had five floors with a 2,250 sq. ft. basement. Taif Al Jorani – 9614 Labette Drive - Saint Louis, MO 63123– 314.359.7040 1 of 2
- 2. • I designed a two-story restaurant in the Mansour district of Baghdad. There I also designed a variety of interfaces and interior design for shops in the area. Training courses: BPI ( Building Performance Institute, Inc ) USA I graduated and got a certificate as ( Building Analyst Professional ) Of October 13, 2010 . Computer Skills: AutoCAD , 3DsMax , Revit , Adobe Photo Shop & Microsoft Office. Affiliations: Registered Architect with the Iraqi Union of Engineers & Architects. References Justin Randall Solar St. Louis Project Manager (573)-819-3952 7020 Chippewa Saint Louis MO 63119 Mohamed T. Al Harash, P.E., C.E. 10567 Homestead Avenue - Saint Louis, MO 63114 Tel: 314.739.0515 - alharash@yahoo.com Taif Al Jorani – 9614 Labette Drive - Saint Louis, MO 63123– 314.359.7040 2 of 2