Analysis Performance of Fast Image Encryption

Perkembangan teknologi mengakibatkan peningkatan kebutuhan pengiriman data melalui media internet. Banyak pengiriman data yang membutuhkan keamanan dalam pengirimannya untuk berbagai keperluan. Enkripsi data merupakan salah satu topic pengamanan yang banyak dilakukan penelitian dengan tujuan untuk mengamankan data yang dikirimkan melalui media internet. Salah satu data yang banyak digunakan adalah data citra. Citra merupakan data yang memiliki kapasitas besar dan memiliki sifat Perulangan yang tinggi sehingga dibutuhkan metode tertentu untuk melakukan proses enkripsi dan dekripsi citra. Permutasi dan difusi merupakan cara yang banyak digunakan untuk melakukan enkripsi citra. Permutasi bertujuan untuk mengacak posisi citra sedangkan difusi merubah nilai citra. Permutasi dan difusi banyak dilakukan sebagai dua tahap yang berbeda sehingga dibutuhkan dua kali pembacaan citra. Sebuah algoritma untuk menggabungkan proses permutasi dan difusi sehingga hanya diperlukan satu kali pembacaan citra untuk melakukan enkripsi telah diajukan. Selain permutasi dan difusi, fungsi chaos juga digunakan dalam algoritma tersebut karena kemampuannya untuk menghasilkan angka random yang sangat sensitif terhadap beberapa parameter. Dengan ide demikian, algoritma akan cepat untuk melakukan proses enkripsi dan dekripsi. Dalam penelitian ini dianalisis kinerja algoritma gabungan permutasi dan difusi menggunakan fungsi chaos. Analisis dilakukan dengan mengimplementasikan algoritma, mendapatkan waktu yang dibutuhkan untuk proses enkripsi dan dekripsi serta membandingkannnya dengan algoritma baku yang telah banyak digunakan, Advanced Encryption Standart (AES)

Empirical Study of Car License Plates Recognition

The number of vehicles on the road has increased drastically in recent years. The license plate is an identity card for a vehicle. It can map to the owner and further information about vehicle. License plate information is useful to help traffic management systems. For example, traffic management systems can check for vehicles moving at speeds not permitted by law and can also be installed in parking areas to se-cure the entrance or exit way for vehicles. License plate recognition algorithms have been proposed by many researchers. License plate recognition requires license plate detection, segmentation, and charac-ters recognition. The algorithm detects the position of a license plate and extracts the characters. Various license plate recognition algorithms have been implemented, and each algorithm has its strengths and weaknesses. In this research, I implement three algorithms for detecting license plates, three algorithms for segmenting license plates, and two algorithms for recognizing license plate characters. I evaluate each of these algorithms on the same two datasets, one from Greece and one from Thailand. For detecting li-cense plates, the best result is obtained by a Haar cascade algorithm. After the best result of license plate detection is obtained, for the segmentation part a Laplacian based method has the highest accuracy. Last, the license plate recognition experiment shows that a neural network has better accuracy than other algo-rithm. I summarize and analyze the overall performance of each method for comparison

EMPATH: A Neural Network that Categorizes Facial Expressions

There are two competing theories of facial expression recognition. Some researchers have suggested that it is an example of "categorical perception." In this view, expression categories are considered to be discrete entities with sharp boundaries, and discrimination of nearby pairs of expressive faces is enhanced near those boundaries. Other researchers, however, suggest that facial expression perception is more graded and that facial expressions are best thought of as points in a continuous, low-dimensional space, where, for instance, "surprise" expressions lie between "happiness" and "fear" expressions due to their perceptual similarity. In this article, we show that a simple yet biologically plausible neural network model, trained to classify facial expressions into six basic emotions, predicts data used to support both of these theories. Without any parameter tuning, the model matches a variety of psychological data on categorization, similarity, reaction times, discrimination, and recognition difficulty, both qualitatively and quantitatively. We thus explain many of the seemingly complex psychological phenomena related to facial expression perception as natural consequences of the tasks' implementations in the brain

Solar Eclipse 2017 Illinois Launches: Temperature, Spectrometer, Video, and Waves

During the August 21, 2017 Solar Eclipse that swept across North America, NearSpace Launch (NSL) took a group of 70 people to Logan College in Carterville, IL, near the center of the Eclipse and we were fortunate to have good viewing. Several balloons, loaded with sensors, were launched, with a follow up calibration launch a few weeks later in addition to ground images. This paper presents the results and observations from the analysis of the data collected from those launches. Payloads and sensors included cameras, spectrometers, temperature sensors, and GPS tracking. The cameras were a live video (1280x720) and HD (1920x1080) video cameras with memory cards, oriented upwards at the Sun’s inclination, and downwards to observe the Moon’s shadow. These cameras had a combination of telephoto lenses and solar filters to view all different types of images (eclipse, shadows, chromosphere, limb, burst, descent). A chromosphere solar image during totality was serendipitously observed from a lake reflection based on the geometry. The spectrometers with 50-100 nm resolution measured electromagnetic radiation absorption lines in the UV and visible light ranges, showing data at different and points in the Eclipse. The temperature sensors data is consistent with the National Weather Service (NWS) troposphere and stratosphere radiosonde predicts, although there are some unique features associated with the eclipse cooling. Fortuitously, one of the balloons was in the tropopause (-73C) during totality and indicated a small temperature drop. There were also different wind effects that were observed through the GPS tracking, both horizontally and vertically

Sciatic nerve sarcoidosis: utility of magnetic resonance peripheral nerve imaging and treatment with radiation therapy

Journal ArticleSarcoidosis may involve both the central and peripheral nervous system, although peripheral nerve manifestations are usually seen late in the disease. In this report, the authors describe a case of sarcoidosis in a 22-year-old woman who presented with a foot drop. Although results of conventional lumbar magnetic resonance (MR) imaging were normal, MR peripheral nerve imaging of the thigh showed a mass in the sciatic nerve indicating tumor. An intraoperative biopsy sample revealed noncaseating granulomas consistent with sarcoid. The patient was treated with steroid drugs to control the manifestations of her disease but exhibited early signs of femoral bone necrosis, which required discontinuation of the steroids. She was then treated with local radiation therapy. At her 2-year follow-up visit the patient demonstrated relief of her symptoms and improvement on MR peripheral nerve imaging. This case demonstrates that sarcoidosis may present with peripheral nerve manifestations. The appearance of a diffusely swollen nerve on MR imaging should prompt clinicians to include sarcoidosis in the differential diagnosis and plan surgery accordingly. Patients who are not responsive to or who are unable to tolerate medical therapy may be treated with radiation therapy

Non-Profit Archival Management: Implementing The Archivists' Toolkit at The Music Maker Relief Foundation

This paper details the process of implementing The Archivists' Toolkit (AT), an open source archival management application, at The Music Maker Relief Foundation (MMRF), a non-profit institution with a significant amount of audiovisual materials of cultural and historical interest. An overview of MMRF's past approach to archival management, its current stage of organizational renovation and development, and the benefits of incorporating new archival practices and standards are discussed. Recommendations are made for future arrangement, description and access to MMRF's archives. The results of this project may potentially be extended to other non-traditional organizations with significant archival holdings

Thin CubeSats and Compact Sensors for Constellations in VLEO to Deep Space

ThinSat form factors have many advantages for constellations and are launched directly from all standard 1U to 27U CubeSat canisters. Currently NSL is completing two 6U constellations for launch in 2023. The Space Weather NASA SBIR Phase II consists of 4 satellites, each with dimension 7.5x10x20cm. Novel and compressed Space Weather instruments are being developed by NSL partners. Each satellite can be divided into two ThinSat sections separated by a 20 cm foldout to serve as a 1) sensor boom, 2) quiet low noise Faraday sensor box, 3) passively cooled from -40 to + 40 C platform, and 4) cleaner sealed sensor environment depending on sensor requirements. The Space Force SBIR Phase II consists of four longer ThinSats with each dimension of 2.5x10x30cm. ThinSats can be connected together to form thicker satellites for larger subsystems and identified as 2T, 3T, 4T, and others. Significant ThinSat advantages include 1) Ease of robotic assembly at lower cost, 2) Larger surface area for solar cells and sensors compared to cubes, 3) Aerodynamic for low altitude ionospheric planetary measurements, 5) Ease for workflow and testing, and 6) Superior low-noise isolation. ThinSats also include 24/7 sat-links using improved Iridium (TX & RX) and previous Globalstar (TX) communication constellations. Recent NSL launches in the past two years will illustrate ThinSat sensor data and orbital results. GEARRS-3, TROOP-1, 2 and 3 launches and NSL ExoSat payload with many miniaturized sensors onboard is scheduled for 2023 launch on NASA EM-1 Deep Space measurements

A Text-Graphics Character CAPTCHA for Password Authentication

Abstract-We propose a new construct, the Text-Graphics Character (TGC) CAPTCHA, for preventing dictionary attacks against password authenticated systems allowing remote access via dumb terminals. Password authentication is commonly used for computer access control. But password authenticated systems are prone to dictionary attacks, in which attackers repeatedly attempt to gain access using the entries in a list of frequentlyused passwords. CAPTCHAs (Completely Automated Public Turing tests to tell Computers and Humans Apart) are currently being used to prevent automated "bots" from registering for email accounts. They have also been suggested as a means for preventing dictionary attacks. However, current CAPTCHAs are unsuitable for text-based remote access. Our TGC CAPTCHA fills this gap. In this paper, we define the TGC CAPTCHA, prove that it is a (secure) CAPTCHA, demonstrate its utility in a prototype based on the SSH (Secure Shell) protocol suite, and provide empirical evidence that the test is easy for humans and hard for machines. We believe that the system will not only help improve the security of servers allowing remote terminal access, but also encourage a healthy spirit of competition in the fields of pattern recognition, computer graphics, and psychology

Automatic morphological trait characterization for corn plants via 3D holographic reconstruction

Plant breeding is an extremely important route to genetic improvements that can increase yield and plant adaptability. Genetic improvement requires careful measurement of plant phenotypes or plant trait characteristics, but phenotype measurement is a tedious and error-prone task for humans to perform. High-throughput phenotyping aims to eliminate the problems of manual phenotype measurement. In this paper, we propose and demonstrate the efficacy of an automatic corn plant phenotyping system based on 3D holographic reconstruction. Point cloud image data were acquired from a time-of-flight 3D camera, which was integrated with a plant rotating table to form a screening station. Our method has five main steps: point cloud data filtering and merging, stem segmentation, leaf segmentation, phenotypic data extraction, and 3D holographic visualization. In an experimental study with five corn plants at their early growth stage (V3), we obtained promising results with accurate 3D holographic reconstruction. The average measurement error rate for stem major axis, stem minor axis, stem height, leaf area, leaf length and leaf angle were at 7.92%, 15.20%, 7.45%, 21.89%, 10.25% and 11.09%, respectively. The most challenging trait to measure was leaf area due to partial occlusions and rolling of some leaves. In future work, we plan to extend and evaluate the usability of the system in an industrial plant breeding setting