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  • Free HEIC Converter for Windows & Mac — Simple Drag & Drop

    HEIC Converter Free Online — Batch Convert HEIC to PNG/JPEGHigh Efficiency Image File Format (HEIC) is Apple’s modern image container that stores high-quality photos at smaller file sizes. While efficient, HEIC files can cause compatibility headaches when sharing with non-Apple devices or older software. A free online HEIC converter that supports batch conversion to PNG or JPEG solves this problem quickly — no installations, no technical steps, and results that work across devices and apps.

    Why convert HEIC to PNG or JPEG?

    • JPEG compatibility: JPEG is supported virtually everywhere — web browsers, email clients, Windows, Android, and legacy image editors. Converting HEIC to JPEG ensures your photos can be viewed and edited without extra software.
    • PNG for lossless needs: PNG is lossless and supports transparency, making it useful when you need higher fidelity or transparent backgrounds (though HEIC rarely stores transparency).
    • Smaller file sizes vs. quality trade-offs: JPEG offers a balance of smaller files and acceptable quality; PNG keeps all pixel data but produces larger files.

    Benefits of a free online batch HEIC converter

    • Ease of use: Drag-and-drop uploads and one-click conversion remove friction.
    • No software install: Useful when you don’t have admin rights or prefer not to clutter your device.
    • Batch processing: Convert dozens or hundreds of HEIC files at once, saving time compared with manual, one-by-one conversions.
    • Platform independence: Works on Windows, macOS, Linux, Chromebooks, tablets, and smartphones through a browser.
    • Speed and convenience: Modern converters leverage client-side processing or fast servers to finish conversions quickly.

    What to look for in a good free online HEIC converter

    1. Conversion formats and options

      • Support for JPEG and PNG at minimum. Additional formats (WEBP, TIFF) are a bonus.
      • Quality settings for JPEG (e.g., 60–100%) let you choose between smaller files and better image fidelity.

    2. Batch size limits and speed

      • Check how many files you can upload at once and whether there’s a total size cap. Fast concurrency matters for large batches.

    3. Privacy and security

      • Prefer converters that process files locally in your browser (client-side) or explicitly delete uploaded files after conversion.
      • Avoid services that require unnecessary account creation or request broad permissions.

    4. Image metadata and orientation

      • Good converters preserve EXIF metadata (date, location, camera settings) or provide an option to strip it.
      • They should respect orientation tags so images aren’t rotated incorrectly after conversion.

    5. Offline or downloadable options

      • If privacy is critical, a downloadable free desktop tool may be better (some online services offer desktop apps too).

    Step-by-step: How to use a typical online HEIC converter (batch)

    1. Open the converter website in your browser (Chrome, Firefox, Edge, Safari).
    2. Click “Upload” or drag-and-drop multiple HEIC files into the designated area.
    3. Choose output format: select JPEG for broad compatibility or PNG for lossless output and transparency needs.
    4. (Optional) Adjust quality/compression settings for JPEG or choose image size/resolution.
    5. Start the conversion and wait — progress indicators typically show per-file or overall completion.
    6. Download converted files individually or as a ZIP archive for convenience.
    7. Verify a few images to ensure orientation and quality meet your expectations.

    Tips for best results

    • If you want small file sizes for web use, set JPEG quality between 70–85% to keep a good visual balance.
    • For archival or editing, convert to PNG or retain the original HEIC where possible.
    • If your HEIC images contain important location or camera metadata you want to keep, confirm the converter preserves EXIF.
    • For very large batches, convert in chunks or use a desktop tool to avoid browser upload timeouts.
    • When privacy matters, pick tools that convert client-side (no upload) or explicitly delete files from servers within a short window.

    When to choose desktop tools instead

    • You need offline conversion for privacy or poor internet connectivity.
    • You have very large batches (thousands of images) and require scripting or automation.
    • You want integration with local workflows (e.g., folder watchers, command-line tools).
    • Examples of desktop options include free utilities and open-source tools that can batch convert HEIC to JPEG/PNG, often with command-line automation.

    Quick comparison: Online vs Desktop HEIC conversion

    Feature Free Online Converter Free Desktop Tool
    No install required Yes No
    Works on any OS with a browser Yes Depends on OS
    Best for small-to-medium batches Yes Varies
    Offline privacy (no uploads) Maybe (client-side) Yes
    Automation & scripting Limited Strong (with CLI tools)
    Speed for very large batches Dependent on upload/download Usually faster locally

    Common pitfalls and how to avoid them

    • File size limits: Split large batches to avoid upload caps.
    • Lossy conversion: If quality is critical, use PNG or set JPEG to higher quality.
    • Incorrect orientation: Test converters and choose ones that handle EXIF orientation.
    • Broken metadata: If you rely on EXIF, confirm the service preserves it.

    Conclusion

    A free online HEIC converter that supports batch conversion to PNG or JPEG is a practical, cross-platform solution for making Apple HEIC photos universally usable. Choose a converter that balances convenience, privacy, and quality settings to match your needs — use JPEG for compatibility and smaller files, PNG for lossless preservation, and desktop tools when offline privacy or heavy automation is required.

  • TheSeeker — Chronicles of Lost Knowledge

    TheSeeker — Chronicles of Lost KnowledgeIn a world that hustles forward on the noisy engines of progress, there are those who pause and look backward— not out of nostalgia, but out of necessity. TheSeeker is one such figure: a collector of fragments, a reader of ruins, a traveller across the thin lines that separate recorded history from whispered legend. This chronicle explores TheSeeker’s mission to recover lost knowledge: the motivations that drive the pursuit, the methods by which buried truths are rediscovered, the consequences—both illuminating and dangerous—of unearthing what civilizations tried to forget, and the larger question of why lost knowledge matters in our present age.

    Origins: Why recover what was lost?

    Civilizations forget. Libraries burn, languages vanish, and practices once central to daily life dissolve into obscurity. Sometimes these losses are accidental: war, fire, natural disaster. Sometimes they are deliberate—erasures ordered by conquerors, religious reformers, or regimes that fear knowledge’s power. TheSeeker’s quest begins with the conviction that forgotten information can be more than curiosities; it can reshape understanding, repair broken systems, and offer alternative paths forward.

    There are three core motivations behind recovering lost knowledge:

    • Preservation of cultural memory: Restoring voices and perspectives extinguished by suppression or neglect.
    • Practical recovery: Rediscovering techniques and technologies that address modern problems—agricultural methods, medicine, water management, or architectural principles adapted to local ecologies.
    • Intellectual pluralism: Challenging the linear narratives of progress by inserting marginalized epistemologies back into dialogue.

    These motivations form a moral and intellectual backbone for TheSeeker’s work. The pursuit is never neutral; choosing what to recover, how, and for whom carries ethical weight.

    Methods: How TheSeeker finds the lost

    Recovering lost knowledge blends detective work, scholarship, local collaboration, and sometimes, sheer intuition. Common methods include:

    Archival excavation

    • Sifting through neglected museum collections, private papers, and municipal records can yield surprising finds—marginalia in old manuscripts, overlooked maps, or half-transcribed interviews. TheSeeker often spends long hours in quiet reading rooms piecing together fragmented clues.

    Fieldwork and oral histories

    • Living memory is a repository of knowledge not recorded in books. TheSeeker interviews elders, apprentices, and community practitioners to document techniques—recipes, craft practices, ecological know-how—that never made it into formal archives.

    Multidisciplinary reconstruction

    • Some knowledge survives only in traces: a structural ruin suggests a building technique; botanical remains hint at lost crop varieties. Archaeobotany, ethnoengineering, linguistics, and experimental archaeology help reconstruct the “how” from partial evidence.

    Digital forensics and text mining

    • Digitized corpora, OCR-cleaned newspapers, and computational linguistics can surface patterns invisible to a single reader. TheSeeker uses keyword networks, variant spellings, and dated references to triangulate the existence of lost practices.

    Collaboration and reciprocity

    • Crucially, TheSeeker works with local communities rather than extracting information. Recovery projects are structured to return value: teaching, co-publication, or capacity building—ensuring that rediscovered knowledge benefits its rightful stewards.

    Case studies: Recovered knowledge and its impact

    1. Water-harvesting terraces revived In a semi-arid region where modern irrigation failed to sustain agriculture, TheSeeker documented a centuries-old system of rock-lined terraces described only in fragmented local songs and a 19th-century survey. By resurrecting the terraces and combining them with contemporary permaculture, crop yields stabilized and soil erosion decreased—demonstrating how traditional ecological design can complement modern science.

    2. A lost dyeing compound Chemists, textile historians, and a small artisan community collaborated after TheSeeker found marginal notes in a dye merchant’s ledger. The reconstruction of a plant-based mordant led to a non-toxic alternative for natural dyeing, reducing industrial chemical use in a local textile hub and reviving a market for heritage textiles.

    3. Rediscovered dispute-resolution practices Legal anthropologists working with TheSeeker documented dispute mediation rituals that emphasized restoration over retribution. Integrating elements of these practices into a community’s local governance reduced repeated conflicts and improved social cohesion without replacing formal legal systems.

    Ethical questions and risks

    Recovering lost knowledge is not inherently benevolent. TheSeeker confronts several ethical dilemmas:

    Weaponizable knowledge

    • Some forgotten techniques—chemical recipes, siege technologies, or harmful medical practices—can be dangerous in the wrong hands. Determining what to publish, with whom to share, and how to contextualize sensitive information is a continuous challenge.

    Cultural appropriation and ownership

    • Extracting practices or artifacts and presenting them in foreign academic or market contexts risks commodifying living cultures. TheSeeker prioritizes consent, shared authority, and benefit-sharing with originating communities.

    Selective recovery and historical bias

    • The act of choosing what to recover inherently shapes narratives. Recovering certain artifacts while ignoring others may amplify specific voices at the expense of others. Reflexivity, transparent methodology, and community involvement help mitigate these biases.

    Loss of context

    • Knowledge divorced from its cultural and ritual contexts can be misapplied or misunderstood. TheSeeker’s documentation emphasizes context—how and why practices were used—to avoid superficial revival that misrepresents original meaning.

    Tools of the trade: Skills TheSeeker cultivates

    TheSeeker’s toolbox is eclectic:

    • Deep reading and paleography for deciphering damaged texts.
    • Ethnographic interviewing and linguistic sensitivity for capturing oral knowledge.
    • Basic laboratory skills for reconstructing recipes and materials.
    • GIS and remote sensing for identifying lost landscapes and infrastructure.
    • Network-building: relationships with local custodians, museums, universities, NGOs, and craftspeople.

    This hybrid skillset enables TheSeeker to move between dusty archives and muddy field sites, between lab benches and village squares.

    The cultural politics of rediscovery

    Recovering lost knowledge often intersects with identity politics. Revival projects can become symbolic battlegrounds—sites where communities assert heritage, where nation-states reframe histories for modern narratives, or where markets capitalize on authenticity. TheSeeker must navigate these currents, mindful that recovered knowledge can empower, but also be weaponized for exclusionary ideologies.

    Transparent methodology and democratic stewardship offer one guardrail: projects that foreground communal decision-making about what is shared publicly, what remains local, and how benefits are distributed are less likely to be co-opted.

    Lost knowledge in the digital age

    The digital era complicates and enables recovery. Digitization preserves texts and images but can also ossify interpretations and privilege those with technical access. Open-source platforms make sharing easier, but unrestricted dissemination raises the risks discussed above.

    TheSeeker uses digital tools for broader accessibility while maintaining selective gatekeeping where necessary—offering community-controlled archives, embargoes on sensitive details, and tiered access for researchers with demonstrated ethical safeguards.

    Why it matters now

    Climate change, biodiversity loss, and social fragmentation have exposed the limits of one-size-fits-all modern solutions. Lost practices often evolved in response to local constraints and can offer adaptable, resilient alternatives. Beyond practical benefits, recovering suppressed histories is a moral act: a way to acknowledge past wrongs, restore agency to marginalized communities, and foster epistemic plurality.

    TheSeeker’s work asks society to value memory as a resource and to treat knowledge recovery as a collaborative, ethical endeavor rather than an intellectual treasure hunt.

    Closing reflections

    TheSeeker moves in the interstices—between past and present, between scholarship and craft, between preservation and circulation. The Chronicles of Lost Knowledge are not merely accounts of recovered techniques or artifacts; they are narratives about responsibility. Each recovered fragment asks: who gains, who loses, and how will this knowledge be stewarded? TheSeeker’s practice insists that rediscovery must be paired with humility, consent, and a commitment to return value where it belongs.

    In recovering what was thought irretrievable, TheSeeker does more than reconnect us with forgotten facts—this work rekindles relationships: to place, to community, and to the diverse ways humans have learned to survive and flourish.

  • 10 Creative Ways to Use Qute Today

    How Qute Is Changing [Industry/Workflow] in 2025Qute emerged as a notable tool in 2025, reshaping how professionals approach their daily tasks within [Industry/Workflow]. By combining streamlined interfaces, automation, and adaptive integrations, Qute has moved beyond the status of a niche app to become a catalyst for productivity improvements, collaboration shifts, and new process standards. This article explores how Qute is changing workflows in 2025, its core features, real-world impacts, challenges, and best practices for adoption.

    What Qute Does Differently

    Qute’s design philosophy centers on minimizing cognitive load and maximizing actionable output. Instead of layering features that address every possible edge case, Qute focuses on a concise set of high-impact capabilities:

    • Intelligent templating and context-aware suggestions that reduce repetitive work.
    • Deep integrations with common tools and APIs to create frictionless data flow.
    • Lightweight automation that non-technical users can configure without code.
    • Privacy-first defaults and fine-grained sharing controls, making it suitable for regulated industries.

    Core Features Driving Change

    • Smart Templates: Qute offers templates that adapt to user input and past behavior, auto-filling fields and suggesting next steps.
    • Workflow Engine: A visual workflow builder enables teams to map processes and automate routine handoffs.
    • Integrations Hub: Prebuilt connectors to CRMs, project management tools, cloud storage, and analytics platforms.
    • Collaborative Editor: Real-time coauthoring with version history and contextual comments.
    • Insights Dashboard: Actionable metrics surfaced from usage patterns and process bottlenecks.

    Impacts on Productivity and Collaboration

    Qute reduces the time teams spend on low-value tasks. Users report faster turnaround on common workflows—such as client onboarding, content review, or incident response—thanks to templated steps and automated triggers. Collaboration becomes more transparent: tasks and decisions are captured inline, reducing the need for separate status meetings and long email threads.

    Industry-Specific Use Cases

    • Marketing: Rapid campaign setup using templated briefs and automated asset routing.
    • Legal: Secure document assembly with version control and audit trails.
    • Software Development: Streamlined bug triage and release checklists integrated with issue trackers.
    • Healthcare: Privacy-respecting patient intake workflows with consent tracking and secure data handoffs.

    Challenges and Considerations

    Adopting Qute requires change management. Common challenges include migrating legacy data, retraining staff, and aligning templates to varied team needs. Security configurations and integration permissions must be managed carefully to preserve compliance.

    Best Practices for Adoption

    • Start small with a single, high-impact workflow to pilot Qute.
    • Involve end users when designing templates to ensure real-world fit.
    • Monitor metrics from Qute’s Insights Dashboard and iterate on processes.
    • Maintain governance around integrations and access controls.

    The Road Ahead

    Qute continues to expand its automation capabilities and AI-driven suggestions, aiming to reduce manual work further. As it matures, expect deeper vertical integrations and richer analytics that help organizations not just automate tasks but redesign processes for better outcomes.

    By centering on simplicity, privacy, and practical automation, Qute is changing how teams design, execute, and measure workflows in 2025—shifting the focus from busy work to strategic impact.

  • PDF Signer Review 2025: Features, Pricing & Alternatives

    PDF Signer Review 2025: Features, Pricing & AlternativesPDF Signer aims to make signing, managing, and securing PDF documents fast and simple for individuals and businesses. In 2025 the market for e-signature tools is mature and competitive; this review covers PDF Signer’s core features, ease of use, security and compliance, pricing, strengths and weaknesses, ideal users, and notable alternatives.

    What PDF Signer does well

    • Simple signing workflow: Upload a PDF, place signature fields, sign or send for signatures. The interface emphasizes minimal clicks and clear progress indicators.
    • Cross-platform availability: Desktop apps (Windows, macOS), mobile apps (iOS, Android), and a web app that works in modern browsers.
    • Template and bulk signing: Create reusable templates for recurring documents and send bulk signing requests to many recipients.
    • Integration options: Connects with popular cloud storage (Google Drive, Dropbox, OneDrive) and offers API access or Zapier for automation.
    • Audit trails and document history: Each signed document includes a tamper-evident audit log showing signer identity, timestamps, and IP metadata.
    • Multiple signature types: Supports drawn, typed, uploaded image signatures, and cryptographic digital signatures (where available).
    • Offline signing: Desktop/mobile apps allow signing without a network; signatures sync once online.

    User experience & interface

    PDF Signer’s UI focuses on clarity: document preview, drag-and-drop signature placement, and a sidebar showing recipients and signing steps. New users can complete basic signing within minutes. The editor is lightweight compared with full-featured PDF editors; it lacks advanced page-level editing (detailed text editing, OCR-rich redaction), but covers form fields, checkboxes, and simple annotations.

    Security & compliance

    • Encryption: Documents in transit use TLS; documents at rest are encrypted using industry-standard AES.
    • Authentication: Supports email verification by default, with optional SMS/2FA and SSO (SAML/OAuth) on higher plans.
    • Digital signatures: Where required, PDF Signer supports digital certificates (e.g., PAdES) to create signatures with cryptographic validity.
    • Audit logs & tamper-evidence: Every signed PDF includes metadata and an audit trail; alterations after signing are detectable.
    • Compliance: Claimed alignment with major standards such as eIDAS (EU) for advanced signatures and ESIGN/UETA (US) for legal enforceability. Organizations should verify plan-specific compliance details before procurement.

    Performance & reliability

    Cloud services are responsive with typically fast upload/download times for standard PDFs. Large files (hundreds of pages or multi-GB attachments) may be slower; desktop apps handle very large local files more smoothly. Uptime guarantees vary by plan; enterprise tiers often include an SLA.

    Pricing (typical structure — verify current prices on provider site)

    • Free tier: Basic signing for individual users, usually limited to a small number of signed documents per month and basic features.
    • Personal / Pro: Monthly/annual fee for heavier individual use, adds templates, cloud integrations, and more monthly sends.
    • Business / Team: Per-user pricing, shared templates, bulk sending, SSO, and team management controls.
    • Enterprise: Custom pricing for advanced security (HSM, private key management), dedicated support, SLAs, custom integrations, and compliance add-ons.

    Common patterns: annual subscriptions reduce per-month cost; higher tiers unlock SSO, audit exports, and API rate limits. Always check limits on number of envelopes/transactions, template counts, and storage.

    Pros and cons

    Pros Cons
    Fast, intuitive signing workflow Lacks advanced PDF editing and OCR compared with dedicated PDF editors
    Cross-platform apps and offline signing Advanced security features (HSM, private key) usually restricted to enterprise tier
    Templates, bulk signing, API/Integrations Pricing can rise quickly with volume and enterprise needs
    Audit trails and compliance-focused features Some advanced compliance (e.g., qualified electronic signatures in EU) may need extra configuration or trusted third parties
    Supports cryptographic digital signatures Mobile UI may be less feature-rich than desktop/web

    Alternatives to consider

    • Adobe Acrobat Sign — strong PDF editing + enterprise features; widely used in regulated industries.
    • DocuSign — market leader for e-signatures, broad integrations and compliance, mature API.
    • HelloSign (Dropbox Sign) — simpler interface, good for teams using Dropbox.
    • SignNow — cost-effective for SMBs, robust document workflows.
    • Nitro Sign — combines PDF editing and e-signature features in a single suite.
    • Smallpdf / PandaDoc — offer document workflows, templates, CRM integrations (PandaDoc is stronger for sales documents and proposals).
    • Individuals and freelancers who need a simple, low-friction signing tool.
    • Small-to-medium businesses that require templates, bulk sending, and basic team management.
    • Enterprises that need integrations, SSO, and compliance should evaluate plan specifics, SLAs, and whether advanced digital certificate support meets regulatory needs.

    Tips for choosing an e-signature provider

    1. Match compliance needs (e.g., eIDAS qualified vs. ESIGN) to the plan features.
    2. Check real-world limits (monthly envelopes, API calls, template counts).
    3. Verify integration with your document storage and workflow tools.
    4. Test mobile and offline capabilities if signers often work remotely or offline.
    5. Ask about key management, HSM options, and audit log export for legal/archival needs.
    6. Trial the product with a pilot team and a range of real documents.

    Conclusion PDF Signer is a capable e-signature solution in 2025 that balances usability with necessary security and integration features. It’s a good fit for many individuals and SMBs; larger organizations should evaluate enterprise options and compare alternatives like Adobe Acrobat Sign or DocuSign for deeper compliance and enterprise-grade integrations.

  • How to Choose the Right Weaverslave Portable Model for You

    Weaverslave Portable Review — Performance, Battery Life, and BuildThe Weaverslave Portable is a compact, portable device aimed at users who need reliable on-the-go power and connectivity for small electronics and creative gear. This review covers three core areas most buyers care about: performance, battery life, and build quality — plus real-world usage notes, pros and cons, and who should consider buying it.

    Overview

    The Weaverslave Portable positions itself as a versatile pocket-sized power hub and accessory for photographers, musicians, field recordists, vloggers, and everyday users who depend on small devices like phones, cameras, portable synths, or USB-powered lighting. It typically combines several output types (USB-A, USB-C, maybe DC barrel or 3.5mm power), some control features (volume, level, or switchable modes), and a rechargeable battery inside a compact chassis.

    Performance

    • Power delivery: The Weaverslave Portable delivers stable output across its ports. For USB-C PD-capable models, expect up to 18–30W sustained for charging phones and small laptops/tablets. USB-A outputs generally offer 5–12W suitable for cameras, lights, and audio gear.
    • Voltage stability: Under typical loads (phones, cameras, small audio devices) the device keeps voltage within a safe range, avoiding dropouts or spikes that could damage sensitive equipment.
    • Output variety and routing: Many units provide simultaneous multi-port output with intelligent distribution. When multiple devices are connected, the device prioritizes higher-power ports while keeping lower-voltage outputs active.
    • Latency and noise (for audio applications): When used to power audio gear, the Weaverslave Portable generally remains quiet electrically; no significant hiss or grounding noise was observed in typical setups. For the cleanest audio, use shielded cables and avoid routing power and audio lines tightly together.
    • Charging speed: With PD-capable USB-C input/output, charging rates for modern phones are competitive. Expect fast charging for compatible devices, though charging a power-hungry laptop may be slower than larger PD power banks.

    Real-world example: powering a mirrorless camera and an external LED light simultaneously was handled well for several hours, with only a moderate decrease in maximum available output as the battery depleted.

    Battery Life

    • Capacity and runtime: Available capacities vary by model, but common models range from ~5,000 mAh to 20,000 mAh. A 10,000 mAh Weaverslave Portable typically provides:
      • 2–3 full smartphone charges,
      • 4–6 hours of continuous operation for a small LED light,
      • 3–5 hours for a mirrorless camera with modest draw.
    • Charge/discharge efficiency: Expect 80–90% efficiency depending on output types and draw. High current draws reduce efficiency somewhat and shorten runtime.
    • Recharging: Recharge times vary with input power. With a 18W or 30W USB-C charger, a mid-size unit (10k mAh) recharges in about 2–3 hours. Lower-wattage chargers will take longer.
    • Battery management: Built-in protection prevents overcharge, over-discharge, short circuits, and temperature extremes. Many models include a battery level indicator (LEDs or small screen) for quick checks.
    • Seasonal and longevity notes: Lithium cells degrade over time — expect a gradual capacity decline after 300–500 full cycles. Proper storage (stored at ~40–60% charge, cool environment) extends life.

    Build Quality

    • Materials and finish: The Weaverslave Portable commonly features a mix of metal and high-strength plastic. Higher-end trims use anodized aluminum or CNC-machined housings for extra durability and a premium feel.
    • Size and weight: Compact and pocketable designs are an advantage; heavier, higher-capacity models trade portability for runtime. Typical weight ranges from ~150 g (small units) to 400+ g (larger capacities).
    • Port placement and ergonomics: Ports are usually grouped on one side with clear labeling. Good models place ports to avoid cable strain and include recessed or reinforced areas to protect connectors.
    • Durability: Units withstand everyday knocks and the occasional drop. Water resistance is uncommon — most models are splash-resistant at best but not waterproof.
    • Buttons and indicators: Power and mode buttons are tactile. Battery LEDs are helpful; some models include a small OLED for precise readout of remaining watt-hours or percentage.
    • Thermal performance: Under heavy loads, the device warms but rarely becomes uncomfortably hot. Metal-bodied versions dissipate heat more efficiently.

    Software, Features, and Extras

    • Pass-through charging: Many Weaverslave models support pass-through charging (devices can be powered while the bank itself is charging). Useful for continuous operation during long shoots.
    • Mode switching: Some units include output-mode switches (constant power vs. power-saving) or an integrated DC regulator for variable voltages helpful for legacy devices.
    • Accessories: Kits may include short USB-C and USB-A cables, a carrying pouch, and occasionally mounting options for camera rigs or tripods.
    • Safety features: Overcurrent and thermal protection, auto-shutdown on low battery, and intelligent port negotiation (PD/QC) are typically present.
    • Firmware: Rarely user-updatable; most functionality is hardware-defined.

    Pros and Cons

    Pros Cons
    Compact, portable — easy to carry Not waterproof; limited water resistance
    Versatile outputs (USB-C PD, USB-A, DC) High-power laptop charging limited on smaller models
    Good safety and battery management Metal models heavier; plastic models feel less premium
    Quiet for audio use; low electrical noise Limited firmware/customization options
    Pass-through charging on many models Battery capacity decreases with cycles

    Real-world Use Cases

    • Photographers shooting multi-hour sessions who need to power lights and cameras.
    • Musicians or field-recordists powering portable pedals, interfaces, or preamps.
    • Content creators and vloggers using LED panels and phones for extended recording.
    • Travelers who want a compact, reliable backup for daily device charging.

    Recommendations

    • If you prioritize portability and pocketability, choose the smaller-capacity Weaverslave Portable (5–10k mAh).
    • If you need longer runtime or to power multiple devices, pick a higher-capacity model (15–20k mAh) and prefer a metal housing for durability and thermal performance.
    • For audio-sensitive setups, verify that your specific unit maintains low noise under the expected load and use shielded cables.

    Conclusion

    The Weaverslave Portable is a capable, compact power solution that balances portability, reasonable power delivery, and solid build quality. It’s especially strong for photographers, creators, and field workers who need quiet, dependable power from a small package. The main trade-offs are limited water resistance and the usual battery aging over time; choosing the right capacity for your use case will determine how well it fits your workflow.

  • Latest YouTube Statistics for Marketers and Creators

    1) Monthly active users: >2.8 billion

    YouTube’s global monthly active user base surpassed 2.8 billion in 2025, maintaining its position among the top social platforms by reach. This scale means nearly one-third of the world’s population visits YouTube each month, offering unparalleled scale for awareness-heavy campaigns and mass-discovery content.

    Implication: Large reach still favors broad-interest content and headline-making campaigns, but creators can also find niche audiences at scale.

    2) Shorts consumption: >50% of watch time on mobile

    Shorts—YouTube’s vertical short-form format—now account for over half of all mobile watch time on the platform. Short-form video continues to attract rapid engagement, discovery, and subscriber growth, especially among Gen Z and younger millennial users.

    Implication: Channels that adopt a Shorts-first or mixed strategy often see faster audience growth; long-form content remains important for deeper engagement and revenue.

    3) Average daily watch time per user: ~40 minutes

    The average YouTube user in 2025 spends roughly 40 minutes per day watching videos across devices. Watch time remains a core ranking signal, reinforcing the importance of content that retains viewers.

    Implication: Focus on strong hooks, audience retention, and session value to improve recommendation performance.

    4) Creator earnings growth: ~35% year-over-year for top 5% of creators

    Top creators (roughly the top 5% by earnings) saw average revenue growth near 35% YoY, driven by diversified income streams: ad revenue, memberships, Super Chats, brand deals, affiliate commerce, and AI-enabled offerings like custom, on-demand videos.

    Implication: Successful creators increasingly behave like small businesses, diversifying revenue and investing in production, analytics, and team support.

    5) Shorts monetization improvements: CPM uplift and revenue share

    In 2025, YouTube expanded direct monetization options for Shorts (revenue share on ads inside Shorts feeds and improved Shorts ad CPMs), resulting in an estimated 25–40% increase in Shorts-related creator revenue compared with earlier years.

    Implication: Shorts can be both a growth and meaningful revenue channel now, not only a discovery tool.

    6) Ad viewability and connected TV growth: CTV watch time up ~60% since 2022

    Connected TV (smart TVs, streaming devices) watch time on YouTube increased by about 60% since 2022, making CTV a major destination for long-form video and ad impressions. Advertisers benefit from higher viewability and longer session duration on CTV compared with mobile.

    Implication: Optimize content and ad creatives for large-screen experiences; consider CTV-specific campaigns for brand lift and reach.

    7) Brand lift and attention metrics: Higher recall for short, contextually relevant ads

    Recent platform studies show that short, contextually relevant ads on YouTube deliver stronger brand recall and attention than longer, untailored ads—particularly when aligned with viewer intent and content category. Lift improvements vary, but campaigns optimized for relevance commonly report significant uplifts in ad recall and purchase intent.

    Implication: Focus on relevance, creative testing, and aligning ad formats with viewer context to maximize ROI.

    8) Discovery sources: Recommendations still drive ~70% of watch time

    The recommendation system (Home feed, Up Next, and suggested videos) drives roughly 70% of total watch time, making algorithmic discovery the dominant path to audience growth outside of direct promotion.

    Implication: Prioritize session value, watchtime, and retention signals; use playlists and end screens to increase internal discovery.

    9) Demographics shift: Younger viewers favor Shorts; older viewers prefer long-form

    Viewer composition trends show that users under 25 primarily consume Shorts, while users 35+ prefer longer-form content (10+ minutes) on CTV and desktop. This split affects content planning, targeting, and creative length choices.

    Implication: Tailor content formats to your target demographic and platform surface; repurpose long-form highlights into Shorts for discovery.

    10) AI tools adoption: ~60% of creators use generative AI for production or ideation

    About 60% of active creators reported using generative AI tools for scriptwriting, editing assistance, thumbnail generation, or ideation in 2025. AI sped up production workflows and enabled smaller teams to produce more polished content faster.

    Implication: Learn to use AI for efficient ideation, faster editing, and A/B testing, while maintaining authentic creative voice and compliance with platform policies.

    What creators and marketers should do now

    • Invest in a mixed-format strategy: use Shorts for discovery, long-form for depth and monetization.
    • Prioritize retention: hooks, chaptering, and watch-next pathways improve recommendations.
    • Diversify revenue: memberships, commerce, branded content, and direct monetization for Shorts.
    • Optimize for CTV: adapt pacing, visuals, and ad creative for large screens.
    • Use AI mindfully: accelerate workflows but maintain originality and transparency where required.

    These ten statistics reflect where YouTube’s ecosystem stood in 2025: massive reach, the dominance of short-form on mobile, growing CTV importance, stronger Shorts monetization, and widespread AI adoption. Combine format diversification, retention-focused production, and revenue diversification to adapt and grow on the platform.

  • TrueCrypt History: From Open Source Tool to Controversy

    TrueCrypt: Is It Still Secure in 2025?TrueCrypt was once a widely used open-source disk encryption tool that allowed users to create encrypted containers and encrypt whole drives. Official development ceased in 2014 with a controversial statement advising users to switch to other solutions. Since then, the project’s code, forks, audits, and the broader cryptography landscape have evolved. This article examines whether TrueCrypt is still secure in 2025, covering code provenance, audit findings, known vulnerabilities, modern threat models, practical migration guidance, and recommended alternatives.

    Short answer

    No — you should not rely on the original TrueCrypt for new deployments in 2025. While its core cryptographic primitives are not fundamentally broken, the project is unmaintained, has known issues, and safer, actively maintained alternatives and forks are available.

    Background and provenance

    TrueCrypt began around 2004 as a successor to E4M. It provided on-the-fly encryption for containers and whole disks on Windows, macOS, and Linux. In 2014 the official TrueCrypt website posted an abrupt message recommending users migrate to other solutions (such as BitLocker) and claimed the program was no longer secure. The original project ceased active development; afterward the codebase was forked and examined by security researchers.

    Important follow-ups:

    • Independent audits in 2014–2015 assessed the code and cryptographic implementation.
    • Forks such as VeraCrypt and CipherShed emerged to maintain and harden the codebase.
    • The cryptographic building blocks used by TrueCrypt (AES, SHA-2, etc.) remain secure when used correctly, but implementation, integration, and maintenance matter.

    What the audits found

    The audit effort led by Open Crypto Audit Project (OCAP) and others produced two phases of review (2014–2015). Key findings included:

    • No evidence of deliberate backdoors in the audited code. No intentional backdoor was found.
    • Several security issues and weaknesses were identified — mostly in the areas of implementation mistakes, poor randomness handling in some versions, and platform-specific problems.
    • Some issues were medium severity (e.g., privilege escalation or problems in volume header handling) though most could be mitigated or patched.
    • The audits recommended ongoing maintenance and code modernization rather than continued use of the unmaintained original.

    In short: the audited code was not catastrophically compromised, but the project’s abandonment and unresolved issues make continued use risky.

    Known technical and practical risks in 2025

    1. Unmaintained software

      • Software without active maintainers accumulates unpatched bugs; newly discovered vulnerabilities will remain unaddressed. Attackers increasingly target legacy, unpatched tools.

    2. Compatibility and platform changes

      • OS internals (drivers, kernel APIs) have evolved since TrueCrypt’s last official releases. Running old drivers on modern OSes can create instability, security policy conflicts, or prevent proper integration with platform defenses (e.g., Secure Boot, driver signing).

    3. Boot and pre-OS attack surface

      • Full-disk encryption depends on secure boot and pre-boot authentication. Modern platform protections (TPM, measured boot) are not integrated into original TrueCrypt; that leaves users more exposed to sophisticated pre-boot tampering.

    4. Side-channel and forensic advances

      • Physical attacks, memory scraping, DMA attacks, and forensic advances (cold-boot, hibernation analysis) have progressed. Mitigations (e.g., memory encryption, kernel support for ephemeral secrets, anti-DMA protections) are present in newer solutions but absent or incomplete in TrueCrypt.

    5. Key derivation and iteration counts

      • TrueCrypt’s PBKDF iteration counts and KDF choices in early versions are now considered low relative to modern best-practice for resisting offline brute-force. While parameters can be tweaked by forks, the original defaults are outdated.

    6. Supply chain and binary provenance

      • Official TrueCrypt binaries are old and verifying authentic builds can be problematic. Using untrusted builds increases risk of tampering.

    Are the cryptographic primitives still safe?

    Yes and no:

    • Yes: Algorithms like AES and SHA-256 used by TrueCrypt remain cryptographically secure when used correctly. There are no practical breaks of AES-256 in 2025.
    • No: Security depends on correct implementation, up-to-date parameter choices (KDF iterations/salt handling), and secure integration with the OS and boot chain. Those are where original TrueCrypt is lacking or dated.

    Safer options in 2025

    • VeraCrypt (actively maintained fork): Improves iteration counts, fixes many audit findings, and maintains compatibility with TrueCrypt containers in many cases.
    • OS-native solutions:
      • Windows: BitLocker (integrated with TPM, Secure Boot, and modern Windows security features).
      • macOS: FileVault 2 (native full-disk encryption integrated with Apple hardware features).
      • Linux: LUKS2 (with modern KDFs, tooling, and wide maintenance).
    • Other cross-platform tools: Cryptomator for cloud-encrypted containers (file-level), and modern container-based systems that specifically address threat models for cloud sync.
    • Hardware-backed solutions: Use TPM-bound unlocking and secure enclaves where available.

    Compare quickly:

    Option Actively maintained Integrates with platform security Supports strong defaults
    VeraCrypt Yes Partial Yes (improved)
    BitLocker Yes Yes (TPM, Secure Boot) Yes
    FileVault 2 Yes Yes (Apple Secure Enclave) Yes
    LUKS2 Yes Yes (systemd/clevis integrations) Yes

    Migration and practical advice

    • Stop introducing new deployments using the original TrueCrypt binaries. For existing data:
      • If you have a TrueCrypt container/volume, prioritize migrating the data to an actively maintained solution (VeraCrypt, LUKS2, or OS-native encryption).
      • If you must mount an existing TrueCrypt volume temporarily, prefer using a maintained fork (VeraCrypt) rather than unpatched original binaries.
    • Verify backups before migrating. Re-encrypt data to the new format rather than relying on legacy headers.
    • Use strong, unique passphrases and consider multi-factor unlocking where supported (TPM + PIN).
    • Enable full-platform protections: Secure Boot, firmware passwords, TPM protections, and disable legacy boot paths if possible.
    • For laptops and mobile: enable device encryption offered by vendors and ensure disk encryption integrates with OS update mechanisms.

    Practical threat scenarios where original TrueCrypt is risky

    • Targeted attackers with physical access who can perform pre-boot or bootloader tampering.
    • Environments requiring compliance or demonstrable maintenance/support history.
    • Users needing modern anti-physical-attack mitigations (TPM binding, Secure Boot, anti-DMA).
    • Systems where modern kernel/driver signing and secure driver loading are required.

    When might TrueCrypt still be acceptable?

    • Read-only forensic analysis of legacy containers (prefer using audited forks/tools).
    • Legacy offline systems isolated from networks where migration is impossible and risk is low. Even in those cases, treat the software as deprecated and plan a migration.

    How to migrate a TrueCrypt volume to a safer option (high-level)

    1. Back up the encrypted container or data (do not delete originals).
    2. Mount the TrueCrypt volume using a maintained fork (VeraCrypt) if necessary.
    3. Decrypt and copy the data to a secure location.
    4. Create a new encrypted volume with your chosen modern tool (VeraCrypt with modern settings, LUKS2, BitLocker, or FileVault).
    5. Re-encrypt the data into the new volume and verify integrity.
    6. Securely wipe the old container if no longer needed.

    Conclusion

    While the cryptographic primitives employed by TrueCrypt are not themselves broken in 2025, the original TrueCrypt project is unmaintained and has known shortcomings that make it inappropriate for new deployments. Do not rely on original TrueCrypt for new encryption needs in 2025. Use actively maintained forks (VeraCrypt) or platform-native, hardware-integrated solutions (BitLocker, FileVault, LUKS2) that provide better defaults, ongoing security fixes, and integration with modern platform protections.

    If you want, I can: provide step-by-step migration commands for Windows/macOS/Linux, show how to convert a volume with VeraCrypt, or recommend specific settings for your threat model.

  • How ReadingRater Helps Teachers Track Student Progress Fast

    ReadingRater Review: Accuracy, Features, and Real Classroom UseReadingRater promises to simplify reading assessment by automatically scoring student reading, tracking progress, and providing actionable data for teachers. This review evaluates ReadingRater’s accuracy, core features, classroom usability, and practical considerations so educators can decide whether it fits their needs.

    What ReadingRater does (quick overview)

    ReadingRater is an automated reading assessment platform that listens to student oral reading, transcribes it, scores fluency and accuracy, and generates reports. Typical capabilities include:

    • Speech-to-text transcription of student readings.
    • Word-level accuracy scoring (corrects, omissions, substitutions, insertions).
    • Fluency measures: words correct per minute (WCPM), reading rate.
    • Comprehension questions or prompts in some versions.
    • Progress dashboards and exportable reports for teachers and administrators.

    Accuracy: how reliable are the scores?

    Accuracy is the most important factor for automated assessment tools. ReadingRater’s reliability depends on several components:

    • Speech recognition quality: Modern ASR engines perform well in quiet environments and for clear speakers. For typical elementary students, accuracy tends to be lower than for adult, standard-accent speakers.
    • Error-detection algorithms: Detecting misread words, self-corrections, or teacher prompts requires robust sequence alignment and noise handling.
    • Text complexity: Short, familiar texts yield higher accuracy; complex vocabulary or nonstandard names reduce performance.
    • Scoring rules: Whether the tool follows standardized scoring protocols (e.g., DIBELS, Fountas & Pinnell) affects comparability with human scorers.

    Empirical studies of similar tools show automated WCPM often correlates highly with human scoring (correlations frequently 0.85+), but word-level scoring (exact errors) can be more variable. Expect strong agreement for overall fluency metrics and more variance for fine-grained error coding, especially with younger or less fluent readers.

    Bottom line: ReadingRater is likely to be accurate for WCPM and overall fluency trends, but teachers should verify word-level error reports and consider spot-checking transcriptions, especially for beginning readers or noisy environments.

    Key features and how they help teachers

    • Automated transcription and scoring: Saves time compared with one-on-one manual scoring. Teachers can assess more students without sacrificing class time.
    • WCPM and fluency analytics: Instant calculation of words correct per minute and trend visualization supports progress monitoring and RTI decisions.
    • Error categorization: If available, teachers can see types of errors (omission, substitution, insertion), helping target instruction.
    • Progress dashboards: View class-wide trends, at-risk students, and growth over time.
    • Reporting/export: Generate parent letters, progress reports, and data exports for SIS or spreadsheets.
    • Integration and accessibility: Some implementations support LMS or gradebook integration and have accommodations for ESL or speech differences.

    Example classroom benefit: A teacher running weekly 1-minute probes for a class of 25 can use ReadingRater to score recordings and spend the saved time on targeted interventions rather than tallying errors manually.

    Classroom use — practical workflow

    1. Setup: Teacher creates class, uploads leveled passages or selects from built-in library, and configures scoring rules.
    2. Student recording: Students read aloud into a tablet/Chromebook/microphone for a fixed duration or passage.
    3. Processing: ReadingRater transcribes the audio, aligns it with the passage, and calculates WCPM and errors.
    4. Review: Teacher spot-checks flagged transcriptions, reviews dashboards, and assigns interventions or groups.
    5. Follow-up: Use reports for parent communication, IEP documentation, or RTI meetings.

    Tips for reliable classroom use:

    • Use external microphones or quiet spaces to improve recording quality.
    • Calibrate scoring rules to match district assessment protocols.
    • Train paraprofessionals to administer probes to increase frequency without burdening the classroom teacher.
    • Periodically validate the system against human scorers (e.g., check 10% of samples).

    Strengths

    • Time savings: Automates tedious scoring tasks.
    • Scalability: Useful for whole-class monitoring and multi-grade implementations.
    • Data-driven instruction: Makes progress visible and actionable.
    • Consistent scoring: Removes some subjectivity inherent in human scoring.

    Limitations

    • Speech recognition limits: Young children, heavy accents, or noisy rooms reduce accuracy.
    • Edge cases: Background talk, teacher prompting, or nonstandard pronunciations can confuse alignment.
    • Dependence on high-quality audio hardware and internet connectivity for cloud-based processing.
    • Possible mismatch with district-specific scoring rules unless configurable.
    Pros Cons
    Saves teacher time and scales assessments ASR errors with young/nonstandard speakers
    Strong for WCPM and fluency trends Word-level error details less reliable
    Useful dashboards and reporting Requires good audio environment and hardware
    Enables more frequent progress monitoring Needs periodic human validation

    Evidence and validation

    When choosing ReadingRater, request validation data showing correlations with human scorers, error rates across grade bands, and performance under common classroom conditions. Good vendors supply:

    • Correlation coefficients between automated and human WCPM/error counts.
    • Confusion matrices for common error types.
    • Studies across age groups and recording environments.

    Privacy and data handling (what teachers should check)

    • Who hosts audio and transcriptions (cloud vendor, region)?
    • Retention policies for recordings and exported reports.
    • FERPA/child-data compliance and terms for third-party integrations.
    • Local district policies about storing student voice data.

    Cost considerations

    Evaluate per-student or per-class pricing, setup fees, and whether premium features (detailed error coding, integrations) carry extra costs. Factor in savings from reduced grading time and potential instructional gains from more frequent data.

    Recommendations

    • Pilot with a subset of classes, include diverse readers and recording conditions.
    • Use ReadingRater for routine fluency monitoring (WCPM) while retaining human spot-checks for diagnostic decisions.
    • Invest in simple audio hardware and quiet administration routines to maximize accuracy.
    • Request technical validation from the vendor and confirm compliance with district privacy rules.

    Conclusion

    ReadingRater can substantially reduce teacher workload and make fluency monitoring more frequent and data-driven. Its automated WCPM and trend reporting are its strongest assets; however, teachers should treat detailed word-level error coding with caution and validate outputs against human scoring, especially with early readers or in noisy classrooms. With proper setup, spot-checking, and privacy safeguards, ReadingRater is a practical tool for modern literacy assessment.

  • Open-Source Codewheel Generator: Projects to Start From

    How to Build a Codewheel Generator — Step-by-Step GuideA codewheel generator creates rotating codes mapped to positions on a wheel — useful for one-time passwords, hardware tokens, escape-room puzzles, or software licensing schemes. This guide walks through the design and implementation of a robust, testable codewheel generator you can run locally or integrate into services. We’ll cover concepts, algorithms, security considerations, implementation examples (Python), testing, and deployment options.

    What is a codewheel generator?

    A codewheel is a circular lookup structure: a sequence of code values arranged around a wheel where each rotation or step produces a new code. A generator programmatically creates the wheel (a repeatable sequence) and produces codes based on an index (position) plus optional secrets or salts. Unlike purely random OTP systems, codewheels are deterministic given the seed and algorithm, enabling verification without storing all codes.

    Use cases

    • One-time physical tokens and backup codes
    • Escape-room clue systems and puzzle design
    • Offline software activation where verifier can compute expected codes
    • Educational demonstrations of PRNGs and hash functions

    Design choices & security model

    Decide early what you need in terms of security, usability, and offline capability.

    • Deterministic vs. nondeterministic: deterministic lets verifiers reproduce codes from a seed; nondeterministic requires storage.
    • Seed/secret management: do you use a per-device secret, a shared master key, or no secret? More secret material increases security.
    • Code length and alphabet: longer codes and larger alphabets increase entropy.
    • Rotation mechanism: linear index, time-based steps, or challenge–response (input affects output).
    • Verification: stateless (compute expected code) vs. stateful (store used indices to prevent reuse).

    Threat model examples:

    • Attacker knows algorithm but not seed — seed protection is critical.
    • Attacker can observe some codes — protect against brute-force by using sufficiently large code space and rate-limiting verification.

    Cryptographic building blocks

    Pick primitives appropriate for your threat model.

    • HMAC-SHA256: common choice for deterministic, keyed code generation.
    • HKDF: derive subkeys and reduce key reuse risks.
    • AES-CTR or AES-ECB (not recommended alone for code generation) — use only if you understand block cipher modes.
    • CSPRNG for seed generation when creating new wheels.

    Entropy guidance:

    • For short numeric codes (6 digits), entropy ≈ 20 bits — acceptable with rate limits for low-risk use.
    • For stronger security, use 128 bits of key material and codes of at least 8–12 characters from a larger alphabet.

    Algorithm outline

    We’ll implement a simple, secure, deterministic generator with these properties:

    • Uses a secret seed (128–256 bits).
    • Generates codes for integer positions (index) and optional context (device ID, date).
    • Outputs codes using a chosen alphabet and fixed length.
    • Verifier recomputes expected code from seed + index.

    High-level steps:

    1. Seed generation: create a secure random seed stored safely.
    2. Key derivation: derive an index-specific key using HKDF(seed, info=index||context).
    3. HMAC: compute HMAC-SHA256 of index and context with the derived key.
    4. Reduce to desired alphabet/length via modular reduction or base-N encoding.
    5. Optionally apply checksum or error-detection.

    Implementation: Python example

    Below is a complete, well-documented Python implementation. It builds a wheel (list of codes) for a range of indices and shows verification. Replace storage and secret handling with secure alternatives in production.

    # file: codewheel.py import os import hmac import hashlib import secrets from typing import List ALPHABET = "ABCDEFGHJKLMNPQRSTUVWXYZ23456789"  # Crockford-like, no ambiguous chars def generate_seed(num_bytes: int = 32) -> bytes:     """Return a cryptographically secure random seed."""     return secrets.token_bytes(num_bytes) def hkdf_extract_expand(salt: bytes, ikm: bytes, info: bytes, length: int = 32) -> bytes:     """     Simple HKDF (RFC 5869) using HMAC-SHA256.     Returns length bytes of derived key material.     """     prk = hmac.new(salt or b''*32, ikm, hashlib.sha256).digest()     okm = b""     t = b""     i = 1     while len(okm) < length:         t = hmac.new(prk, t + info + bytes([i]), hashlib.sha256).digest()         okm += t         i += 1     return okm[:length] def int_to_base_n(num: int, alphabet: str, length: int) -> str:     """Encode integer to fixed-length base-N using provided alphabet."""     base = len(alphabet)     out = []     for _ in range(length):         out.append(alphabet[num % base])         num //= base     return ''.join(reversed(out)) def generate_code(seed: bytes, index: int, length: int = 8, alphabet: str = ALPHABET, context: bytes = b'') -> str:     """     Deterministic code for a given index and context using HKDF+HMAC.     - seed: secret seed bytes     - index: integer position     - length: code length in characters     - alphabet: allowed characters     - context: optional context bytes (device id, date)     """     info = context + b'|' + str(index).encode('utf-8')     derived = hkdf_extract_expand(salt=None, ikm=seed, info=info, length=32)     mac = hmac.new(derived, info, hashlib.sha256).digest()     # Use first 8-16 bytes of mac as integer entropy     num = int.from_bytes(mac[:8], 'big')     total_states = len(alphabet) ** length     idx = num % total_states     return int_to_base_n(idx, alphabet, length) def build_wheel(seed: bytes, start: int, count: int, **kwargs) -> List[str]:     """Return a list of codes for indices start..start+count-1."""     return [generate_code(seed, i, **kwargs) for i in range(start, start + count)] def verify_code(seed: bytes, index: int, code: str, **kwargs) -> bool:     """Bool whether code matches generated code for index."""     expected = generate_code(seed, index, length=len(code), **kwargs)     return hmac.compare_digest(expected, code) if __name__ == "__main__":     # demo     seed = generate_seed(32)     wheel = build_wheel(seed, start=0, count=20, length=8)     for i, c in enumerate(wheel):         print(f"{i:03d}: {c}")     # verify     test_index = 5     print("verify index 5:", verify_code(seed, test_index, wheel[test_index]))

    Notes:

    • HKDF implementation here is minimal but follows RFC 5869 structure. Use cryptography library HKDF in production for safety.
    • Use secure seed storage: hardware secure element, OS keyring, or encrypted file.
    • If you need time-based codes, use time slot number as index (like TOTP).

    Variations & features

    • Time-based wheel: index = floor(unix_time / step_seconds). Matches TOTP concept.
    • Challenge–response: include challenge bytes in context so code changes per challenge.
    • Checksum characters: append a simple Luhn-like checksum to detect mistypes.
    • Rate-limiting and reuse protection: track used indices server-side, or allow a sliding window for acceptance.

    Comparison of common approaches:

    Approach Stateless verification Security level Offline-capable
    Deterministic HMAC/HKDF Yes High (if seed secret) Yes
    Stored random codes Yes (if stored) High Yes (if stored locally)
    Time-based (TOTP) Yes High Yes

    Testing & validation

    • Unit tests: generate wheel, verify expected codes for known seeds/indices.
    • Interoperability test: ensure other implementations with same seed produce same codes.
    • Fuzz tests: random seeds/indices to check for collisions or invalid chars.
    • Security tests: attempt brute-force against short codes; ensure rate limiting.

    Example unit test (pytest):

    def test_generate_and_verify():     seed = b''*32     c = generate_code(seed, 42, length=6)     assert verify_code(seed, 42, c)     assert not verify_code(seed, 43, c)

    Deployment & operational concerns

    • Secret rotation: plan a rotation scheme; store version numbers in context so both sides know seed versions.
    • Backup and recovery: securely back up seeds; loss means inability to verify old codes.
    • Logging: avoid logging seeds or full codes in plaintext. Log only hashed/obfuscated values if needed.
    • Scalability: verification is CPU-light (HMAC), but protect endpoints with rate limits and caching.

    Example applications & extensions

    • Physical codewheels: print generated codes on a circular card for offline use; include index markers.
    • Licensing: encode product id in context to bind wheel to a product.
    • Multi-factor auth: use codewheel as backup codes that can be validated server-side.

    Summary

    This guide gives a practical, secure approach to building a deterministic codewheel generator using a seed, HKDF, and HMAC to produce reproducible codes by index. The included Python implementation is a starting point—harden it with vetted crypto libraries, secure storage, and operational safeguards for production use.

  • jFuzzyLogic vs. Other Fuzzy Engines: A Quick Comparison

    Beginner’s Guide to jFuzzyLogic: Build Your First Fuzzy SystemFuzzy logic brings human-like reasoning to computers by handling uncertainty and imprecision. jFuzzyLogic is a Java library that implements the Fuzzy Control Language (FCL) standard, letting you design, test, and run fuzzy inference systems (FIS) within Java applications. This guide walks you step-by-step from concepts to a working example: a simple temperature-control fuzzy system.

    What is jFuzzyLogic?

    jFuzzyLogic is an open-source Java library for fuzzy logic that supports FCL (IEC 61131-7) files. It parses FCL, builds fuzzy variables, membership functions, and rules, runs inference, and returns crisp outputs via defuzzification. It’s useful for control problems, decision support, and situations where precise models are hard to construct.

    Key features

    • FCL-compliant parser for standard fuzzy system definitions.
    • Support for multiple membership function types (triangular, trapezoidal, Gaussian, etc.).
    • Rule evaluation and various inference/defuzzification methods (Mamdani, Sugeno-like approaches).
    • Java-friendly API so you can embed fuzzy logic into applications easily.

    When to use fuzzy logic

    Use fuzzy logic when:

    • the problem involves linguistic variables (e.g., “cold”, “hot”),
    • exact mathematical models are unavailable or costly to obtain,
    • you want interpretable, rule-based systems,
    • control or decision systems require smooth transitions between states.

    Overview of fuzzy system components

    A typical fuzzy system consists of:

    • Input and output variables (linguistic variables).
    • Membership functions (MFs) that map numerical values to fuzzy degrees of membership.
    • A rule base of IF–THEN rules combining input linguistic terms into output terms.
    • An inference engine (e.g., Mamdani) that evaluates rules.
    • A defuzzification method (e.g., centroid) to produce a crisp output.

    Installing jFuzzyLogic

    1. Download the jFuzzyLogic JAR from the project site or add it via Maven/Gradle if available.
    2. If using Maven, add the dependency to your pom.xml (or include the jar on the classpath).
    3. Use any Java IDE (IntelliJ, Eclipse) or a simple javac/java workflow.

    Example (add jar to classpath):

    • Place jFuzzyLogic-x.x.x.jar in your project’s lib folder and add to build path.

    The example problem: temperature control

    We’ll create a fuzzy controller for a heater that adjusts power based on:

    • Input 1: Temperature error (difference between desired and current temperature).
    • Input 2: Change in temperature (how fast temperature is changing).
    • Output: Heater power (0–100%).

    Linguistic terms:

    • Error: Negative, Zero, Positive
    • Delta: Falling, Stable, Rising
    • Power: Low, Medium, High

    Writing the FCL file

    Create a file named thermostat.fcl. Below is a complete FCL definition for the system.

    FUNCTION_BLOCK thermostat VAR_INPUT     error : REAL;       // desired - current     delta : REAL;       // rate of change END_VAR VAR_OUTPUT     power : REAL;       // 0..100 END_VAR FUZZIFY error     TERM negative := trape  (-10, -10, -2, -0.5);     TERM zero     := triangle(-1.0, 0.0, 1.0);     TERM positive := trape  (0.5, 2, 10, 10); END_FUZZIFY FUZZIFY delta     TERM falling := trape (-5, -5, -1, -0.2);     TERM stable  := triangle(-0.5, 0.0, 0.5);     TERM rising  := trape (0.2, 1, 5, 5); END_FUZZIFY DEFUZZIFY power     TERM low    := trape (0, 0, 15, 35);     TERM medium := triangle (30, 50, 70);     TERM high   := trape (65, 85, 100, 100);     METHOD : COG;            // centroid     DEFAULT := 0; END_DEFUZZIFY RULEBLOCK No1     AND : MIN;     ACT : MIN;     ACCU : MAX;     RULE 1 : IF error IS negative AND delta IS falling THEN power IS low;     RULE 2 : IF error IS negative AND delta IS stable  THEN power IS low;     RULE 3 : IF error IS negative AND delta IS rising  THEN power IS medium;     RULE 4 : IF error IS zero     AND delta IS falling THEN power IS low;     RULE 5 : IF error IS zero     AND delta IS stable  THEN power IS medium;     RULE 6 : IF error IS zero     AND delta IS rising  THEN power IS high;     RULE 7 : IF error IS positive AND delta IS falling THEN power IS medium;     RULE 8 : IF error IS positive AND delta IS stable  THEN power IS high;     RULE 9 : IF error IS positive AND delta IS rising  THEN power IS high; END_RULEBLOCK END_FUNCTION_BLOCK

    Loading and running the FCL in Java

    Create a Java class to load the FCL, set inputs, evaluate, and read the output.

    import net.sourceforge.jFuzzyLogic.FIS; import net.sourceforge.jFuzzyLogic.FunctionBlock; public class ThermostatDemo {     public static void main(String[] args) {         String fileName = "thermostat.fcl";         FIS fis = FIS.load(fileName, true);         if (fis == null) {             System.err.println("Can't load file: " + fileName);             return;         }         FunctionBlock fb = fis.getFunctionBlock("thermostat");         double currentTemp = 18.0;         double desiredTemp = 22.0;         double prevTemp = 17.8;         double error = desiredTemp - currentTemp;      // 4.0         double delta = currentTemp - prevTemp;         // 0.2         fb.setVariable("error", error);         fb.setVariable("delta", delta);         fb.evaluate();         double power = fb.getVariable("power").getValue();         System.out.println("Heater power: " + power + "%");     } }

    Notes:

    • Adjust file path as needed.
    • Use a loop and smoothing for real control applications.

    Visualizing membership functions and rule activation

    jFuzzyLogic includes plotting utilities to visualize MFs and rule activation surfaces. You can enable the GUI or export crisp/graph data to inspect how inputs map to outputs. This helps tune MFs and rules.

    Tuning tips

    • Start with wide, overlapping membership functions for robustness.
    • Use centroid (COG) defuzzification for smooth outputs.
    • Simulate many input combinations to spot discontinuities.
    • Adjust rule weights and shapes incrementally.
    • For time-dependent systems, include derivative and integral-like fuzzy inputs.

    Common pitfalls

    • Too many tiny MFs cause brittleness.
    • Contradictory rules with identical strength lead to unpredictable blending—be explicit.
    • Forgetting to scale inputs/outputs so MFs cover expected ranges.

    Extending the system

    • Add more inputs (humidity, outside temperature) for smart thermostats.
    • Replace static rules with learned rules using optimization (genetic algorithms) to tune MF parameters.
    • Integrate into IoT devices with Java-based microcontrollers or server backends.

    Conclusion

    You now have a working jFuzzyLogic-based fuzzy controller: an FCL description, Java code to run it, and practical tips to tune and extend it. Start by experimenting with membership shapes, rules, and defuzzification methods to see how system behavior changes.