Hexadecimal to decimal conversion
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ADVXAI IN MALWARE ANALYSIS FRAMEWORK: BALANCING EXPLAINABILITY WITH SECURITYijscai With the increased use of Artificial Intelligence (AI) in malware analysis there is also an increased need to
understand the decisions models make when identifying malicious artifacts. Explainable AI (XAI) becomes
the answer to interpreting the decision-making process that AI malware analysis models use to determine
malicious benign samples to gain trust that in a production environment, the system is able to catch
malware. With any cyber innovation brings a new set of challenges and literature soon came out about XAI
as a new attack vector. Adversarial XAI (AdvXAI) is a relatively new concept but with AI applications in
many sectors, it is crucial to quickly respond to the attack surface that it creates. This paper seeks to
conceptualize a theoretical framework focused on addressing AdvXAI in malware analysis in an effort to
balance explainability with security. Following this framework, designing a machine with an AI malware
detection and analysis model will ensure that it can effectively analyze malware, explain how it came to its
decision, and be built securely to avoid adversarial attacks and manipulations. The framework focuses on
choosing malware datasets to train the model, choosing the AI model, choosing an XAI technique,
implementing AdvXAI defensive measures, and continually evaluating the model. This framework will
significantly contribute to automated malware detection and XAI efforts allowing for secure systems that
are resilient to adversarial attacks.
Level 1-Safety.pptx Presentation of Electrical Safety
Level 1-Safety.pptx Presentation of Electrical SafetyJoseAlbertoCariasDel Level 1-Safety.pptx Presentation of Electrical Safety
Lecture 13 (Air and Noise Pollution and their Control) (1).pptx
Lecture 13 (Air and Noise Pollution and their Control) (1).pptxhuzaifabilalshams (Air and Noise Pollution and their Control)
Raish Khanji GTU 8th sem Internship Report.pdf
Raish Khanji GTU 8th sem Internship Report.pdfRaishKhanji This report details the practical experiences gained during an internship at Indo German Tool
Room, Ahmedabad. The internship provided hands-on training in various manufacturing technologies, encompassing both conventional and advanced techniques. Significant emphasis was placed on machining processes, including operation and fundamental
understanding of lathe and milling machines. Furthermore, the internship incorporated
modern welding technology, notably through the application of an Augmented Reality (AR)
simulator, offering a safe and effective environment for skill development. Exposure to
industrial automation was achieved through practical exercises in Programmable Logic Controllers (PLCs) using Siemens TIA software and direct operation of industrial robots
utilizing teach pendants. The principles and practical aspects of Computer Numerical Control
(CNC) technology were also explored. Complementing these manufacturing processes, the
internship included extensive application of SolidWorks software for design and modeling tasks. This comprehensive practical training has provided a foundational understanding of
key aspects of modern manufacturing and design, enhancing the technical proficiency and readiness for future engineering endeavors.
Building Security Systems in Architecture.pdf
Building Security Systems in Architecture.pdfrabiaatif2 Building security systems are essential for protecting people, property, and assets within a structure. These systems include a range of technologies and strategies such as surveillance cameras (CCTV), access control systems, alarm systems, security lighting, and motion detectors. Modern security solutions often integrate smart technology, allowing remote monitoring and real-time alerts through mobile devices. Access control systems, like key cards or biometric scanners, ensure that only authorized individuals can enter certain areas, enhancing both safety and privacy. Alarm systems, whether triggered by unauthorized entry, fire, or environmental hazards, play a critical role in emergency response. Additionally, video surveillance acts as both a deterrent and a tool for investigating incidents. An effective building security system is carefully planned during the design phase, taking into account the building's size, purpose, and potential risks. Ultimately, robust security systems are vital for ensuring peace of mind, protecting lives, and preserving valuable assets.
IntroSlides-April-BuildWithAI-VertexAI.pdf
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"Heaters in Power Plants: Types, Functions, and Performance Analysis"
"Heaters in Power Plants: Types, Functions, and Performance Analysis"Infopitaara This presentation provides a detailed overview of heaters used in power plants, focusing mainly on feedwater heaters, their types, construction, and role in improving thermal efficiency. It explains the difference between open and closed feedwater heaters, highlights the importance of low-pressure and high-pressure heaters, and describes the orientation types—horizontal and vertical.
The PPT also covers major heater connections, the three critical heat transfer zones (desuperheating, condensing, and subcooling), and key performance indicators such as Terminal Temperature Difference (TTD) and Drain Cooler Approach (DCA). Additionally, it discusses common operational issues, monitoring parameters, and the arrangement of steam and drip flows.
Understanding and maintaining these heaters is crucial for ensuring optimum power plant performance, reducing fuel costs, and enhancing equipment life.
Data Structures_Searching and Sorting.pptx
Data Structures_Searching and Sorting.pptxRushaliDeshmukh2 Sorting Order and Stability in Sorting.
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Insertion Sort,
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Merge Sort,
Radix Sort, and
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Mirada a 12 proyectos desarrollados con BIM.pdf
Mirada a 12 proyectos desarrollados con BIM.pdftopitodosmasdos Presentación sobre los pasos iniciales de la metodología BIM
Development of MLR, ANN and ANFIS Models for Estimation of PCUs at Different ...
Development of MLR, ANN and ANFIS Models for Estimation of PCUs at Different ...Journal of Soft Computing in Civil Engineering Passenger car unit (PCU) of a vehicle type depends on vehicular characteristics, stream characteristics, roadway characteristics, environmental factors, climate conditions and control conditions. Keeping in view various factors affecting PCU, a model was developed taking a volume to capacity ratio and percentage share of particular vehicle type as independent parameters. A microscopic traffic simulation model VISSIM has been used in present study for generating traffic flow data which some time very difficult to obtain from field survey. A comparison study was carried out with the purpose of verifying when the adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and multiple linear regression (MLR) models are appropriate for prediction of PCUs of different vehicle types. From the results observed that ANFIS model estimates were closer to the corresponding simulated PCU values compared to MLR and ANN models. It is concluded that the ANFIS model showed greater potential in predicting PCUs from v/c ratio and proportional share for all type of vehicles whereas MLR and ANN models did not perform well.
Avnet Silica's PCIM 2025 Highlights Flyer
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ELectronics Boards & Product Testing_Shiju.pdf
ELectronics Boards & Product Testing_Shiju.pdfShiju Jacob This presentation provides a high level insight about DFT analysis and test coverage calculation, finalizing test strategy, and types of tests at different levels of the product.
Taking AI Welfare Seriously, In this report, we argue that there is a realist...
Taking AI Welfare Seriously, In this report, we argue that there is a realist...MiguelMarques372250 In this report, we argue that there is a realistic possibility that some AI systems
will be conscious and/or robustly agentic in the near future. That means that the
prospect of AI welfare and moral patienthood — of AI systems with their own
interests and moral significance — is no longer an issue only for sci-fi or the
distant future. It is an issue for the near future, and AI companies and other actors
have a responsibility to start taking it seriously. We also recommend three early
steps that AI companies and other actors can take: They can (1) acknowledge that
AI welfare is an important and difficult issue (and ensure that language model
outputs do the same), (2) start assessing AI systems for evidence of consciousness
and robust agency, and (3) prepare policies and procedures for treating AI systems
with an appropriate level of moral concern. To be clear, our argument in this
report is not that AI systems definitely are — or will be — conscious, robustly
agentic, or otherwise morally significant. Instead, our argument is that there is
substantial uncertainty about these possibilities, and so we need to improve our
understanding of AI welfare and our ability to make wise decisions about this
issue. Otherwise there is a significant risk that we will mishandle decisions about
AI welfare, mistakenly harming AI systems that matter morally and/or mistakenly
caring for AI systems that do not.
Development of MLR, ANN and ANFIS Models for Estimation of PCUs at Different ...
Development of MLR, ANN and ANFIS Models for Estimation of PCUs at Different ...Journal of Soft Computing in Civil Engineering
Ad
Hexadecimal to decimal conversion
- 1. Hexadecimal Number to Decimal Number Conversion Mukesh N. Tekwani 4
- 2. To speed up calculations, you may want to remember these powers of 16: 160 = 1 161 = 16 162 = 256 163 = 4096 164 = 65536 1 16 = 0.0625 = 6.25 x 10-2 1 162 = 0.0039 = 3.9 x 10-3 1 163 = 0.000244 = 2.44 x 10-4 Hexadecimal Numbers – Power Tip Mukesh N. Tekwani
- 3. Hexadecimal Number to Decimal Number Conversion – Example 1 Convert the hexadecimal number (B41A)16 to its decimal equivalent. Solution: In this example, the LSD has the weight 160, the next digit has weight 161, and then the MSD has the weight 163. (B41A)16 = (B x 163) + (4 x 162) + (1 x 161) + (A x 160) (B41A)16 = (11 x 4096) + (4 x 256) + (1 x 16) + (10 x 1) (B41A)16 = 45056 + 1024 + 16 + 10 = (46106)10 (B41A)16 = (46106)10 Mukesh N. Tekwani LSDMSD Hexadecimal Number Decimal Number 0, 1, 2,…9 0, 1, 2,…9 A 10 B 11 C 12 D 13 E 14 F 15
- 4. Convert the hexadecimal number (CAB.13)16 to its decimal equivalent. Convert the integral part CAB to decimal: (CAB)16 = (C x 162) + (A x 161) + (B x 160) (CAB)16 = (12 x 162) + (10 x 161) + (11 x 160) (CAB)16 = (12 x 256) + (10 x 16) + (11 x 1) (CAB)16 = (3072) + (160) + (11) (CAB)16 = (3243)10 Convert the fractional part (0.13) to decimal: (0.13)16 = 1 16 + 3 162 (0.13)16 = 0.0625 + 0.01172 (0.13)16 = (0.07422)10 Hexadecimal Number to Decimal Number Conversion – Example 2 Mukesh N. Tekwani So (CAB.13)16 = (3243.07422)10