הפקולטה למתמטיקה ולמדעי הטבע

ביה”ס להנדסה ולמדעי המחשב ע”ש רחל וסלים בנין

טקס הצגת פרוייקטים

מחזור י"דחוגי הנדסת חשמל ומחשבים

וחלוקת פרסיהמרכז לחדשנות בהנדסה ובמדעי המחשב

ע”ש פיטר ברויידא

יום שלישי, ח' בסיון תשע"ו 14.6.2016

הפקולטה למתמטיקה ולמדעי הטבעביה”ס להנדסה ולמדעי המחשב ע”ש רחל וסלים בנין

מתכבדים להזמינך לטקס הצגת פרויקטים

של תלמידי החוגים להנדסת חשמל ומחשבים

המפגש יתקיים ביום שלישי, ח' בסיון, תשע"ו 14.6.2016 בין השעות 16:00-19:30

בבניינים ע"ש רוטברג, ביה"ס להנדסה ולמדעי המחשב, קריית אדמונד י' ספרא, גבעת רם, ירושלים.

הזמנה זו מהווה אישור כניסה לתחומי הקמפוס

סדר יום:16:00-17:30 תצוגת פוסטרים

17:30-18:30 התכנסות באודיטוריום18:30-19:30 כיבוד

התכנסות: ברכות-פרופ' יאיר וייס

ראש ביה"ס להנדסה ולמדעי המחשב ע"ש רחל וסלים בנין

פרופ' עמי ויזל ראש החוג להנדסת חשמל ומחשבים עם התמחות בהנדסת מחשבים

פרופ' יוסי פלטיאל ראש החוג להנדסת חשמל ומחשבים עם התמחות

באופטואלקטרוניקה ומיקרואלקטרוניקה

פרופ' אהרון אגרנט מנהל מרכז ברויידא לחדשנות בהנדסה ובמדעי המחשב

הצגת שני פרויקטים מובילים חלוקת פרסים לפרויקטים מצטיינים

הטקס נערך בחסות יישום, החברה לפיתוח המחקר של האוניברסיטה העברית, לייטריקס,

והמרכז לחדשנות בהנדסה ומדעי המחשב ע"ש פיטר ברויידא

רשימת החוגיםהחוג למדעי המחשב

ראש החוגdaphna@cs.huji.ac.il :פרופ’ דפנה וינשל טל’ 02-5494542 דואל

רכזת לימודי הבוגרmiriame@savion.huji.ac.il :גב’ מרים אדרי טל’ 02-5494501 דואל

רכזת לימודים לתארים מתקדמיםhagity@savion.huji.ac.il :גב’ חגית יער-און טל’ 02-5494504 דואל

החוגים להנדסת חשמל ומחשבים

ראש החוג להנדסת חשמל ומחשבים עם התמחות בהנדסת מחשביםamiw@cs.huji.ac.il :פרופ' עמי ויזל טל' 02-5494539 דואל

ראש החוג להנדסת חשמל ומחשבים עם התמחות באופטואלקטרוניקה ומיקרואלקטרוניקהpaltiel@cc.huji.ac.il :פרופ’ יוסי פלטיאל טל’ 02-6585760 דואל

רכזת החוג )בשני המסלולים(

hilaha@savion.huji.ac.il :גב’ הילה חיו-דנין טל’ 02-5494502 דואל

החוג לביולוגיה חישובית )מסלול ישיר למוסמך(

ראשי החוג למדעי המחשב ולביולוגיה חישוביתmichall@cc.huji.ac.il :פרופ’ מיכל ליניאל טל’ 02-6585425 דואל

tommy@cs.huji.ac.il :ד"ר תומי קפלן טל' 02-5494506 דואל

רכזת החוגhilaha@savion.huji.ac.il :גב’ הילה חיו-דנין טל’ 02-5494502 דואל

החוג לפיסיקה יישומית )לימודי מוסמך(

ראש החוגpaltiel@cc.huji.ac.il :פרופ’ יוסי פלטיאל טל’ 02-6585760 דואל

רכזת החוגhagity@savion.huji.ac.il :גב’ חגית יער-און טל’ 02-5494504 דואל

החוג לביו הנדסה )מסלול ישיר לדוקטורט(ראש החוג

ynahmias@cs.huji.ac.il :דר’ קובי נחמיאס טל’ 02-5494550 דואל

רכזת החוגhagity@savion.huji.ac.il :גב’ חגית יער-און טל’ 02-5494504 דואל

מזכירה לענייני הוראה:

yaeli@cs.huji.ac.il :גב’ יעל בן לולו טל’ 02-5494513 דואל

Real-Time Mobile Based Gaze Tracking Imagine that you could look at your computer and nod and it would pause your movie. Or you're an advertiser and you could know how long a user had looked at your ad. Or you're an educator and you could know how long a pupil spent trying to figure out certain words. Today almost everyone has a mobile device (tablet, mobile phone etc.) and the primary mode of input is through touch. To enhance the depth and meaning of input we used the existing hardware of a tablet and add another dimension for feedback - sight.We built a flexible package that can operate with any existing application. It informs the application what point on the screen the user is gazing at. This technology gives feedback based not only on where a user is looking, but also how long the user looks at that spot.The process of determining the user’s gaze identifies exactly where the user is looking and is broken down into 3 main processes.Identifying the user’s face in the image using the front facing camera. Determining an initial estimate of the gaze point by calculating the pose (face direction relative to the camera). Correcting the gaze point estimate by factoring in the position of the user's pupils relative to the center of the eye.This technology can be applied to a broad spectrum of educational and recreational fields, such as analyzing students’ reading abilities, advertising, interactive gaming, and reading to a visually impaired person to name a few. To demonstrate the concept, we built an interactive game that works solely on the point of the screen where the user is looking.

Project membersChayim Ehrman chayim.ehrman@mail.huji.ac.ilZeev Adelman zeev.adelman@mail.huji.ac.il

SupervisorProf. Shmuel Peleg, The Hebrew University of Jerusalem

Voice ModificationIn order to change a source voice to a target voice a simplistic approach of storing pairs of source-target phonemae, identifying the source phonemae in the input signal and replacing them with the corresponding target phonemae can be taken, but results in an incontinuous signal which doesn’t sound as if the target has spoken it naturally.This project examines the possibility of improving this simplistic approach by using the reference signal of the target voice in a transformation applied on the source signal, yielding vocal similarities with the target voice yet keeping the continuity and rhythm of the source speaker.

Project membersYehuda Babayof yehuda.babayof@mail.huji.ac.ilBoris Talesnik boris.talesnik@mail.huji.ac.il

SupervisorMr. Stas Tiomkin, The Hebrew University of Jerusalem

4 | | 3

Audio-Visual Speech Enhancement Using Deep Learning

Speech enhancement systems aim to improve the quality and intelligibility of speech in a speech communication application, such as mobile phones, VoIP, teleconferencing systems, speech recognition and hearing aids.Our project's main goal is to exploit visual data in order to expand the capabilities of a speech enhancement system. As many such systems today contain cameras (such as mobile phones, laptops, etc.), our project has direct practical applicability.We aim to demonstrate that these systems can be improved by integrating advanced tools from the field of Computer Vision into the speech enhancement process.Our project's main challenges were training a Convolutional Neural Network (CNN) to detect periods of voice activity when given consecutive video frames of a speaker's lips, and integrating this network into a speech enhancement system.Our trained neural network reached high accuracy results, and its effect is demonstrated in a speech enhancement system.

Project membersMoshe Mandel moshe.mandel@mail.huji.ac.ilNofar Noy nofar.noy@mail.huji.ac.il

SupervisorMr. Ofer Springer, The Hebrew University of Jerusalem

Intuitive Real Time Music DeveloperOur use of desktop can be much more efficient and exciting since we can make "smart" tools. For example, the desktop can gather information about the objects that are stored there, and imply actions to help us in work. We decided to implement this idea for music creation.Music creation for people who do not have experience using music software can be frustrating and difficult to learn. The unique hardware for musicians can be expensive as well, so the average person cannot make music easily without investing a lot of time and money. Our goal is to make an accessible, intuitive tool for creating and editing music by the means that we mentioned above. We use a simple camera and projector that everyone can have at home. With image processing we can recognize barcodes, position and orientation of objects. As we analyze the results, we produce feedback that makes sound and projection.We built a prototype with a few basic features, but this tool can be extended to include more functionality.While working on the project we faced two main issues: First, building and stabilizing the physical part, namely the table and hardware, in a way that allows us to get good image to process and recognize our elements.Second, writing software that ties together all the parts of program that we using in our project.

Project membersNeria Saada neria.saada@mail.huji.ac.il Issack Rosenberg issack.rosenberg@mail.huji.ac.il

SupervisorsZiv Barcesat, YerushaLabDr. Amit Zoran, The Hebrew University of Jerusalem

6 | | 5

Electro-Optic Modulation and Switching at 2μ WavelengthsLasers operating at the 2 μm spectral range are attractive candidates for developing a broad range of applications including LIDAR, micro-surgery, transparent plastics processing, and free space communication. Many of these applications favor operation with pulses with high energy at fast repetition rates. The aim of my project is to construct an electro-optic modulator for a 2μ wavelength laser, which can be integrated into the laser cavity for implementing active Q-switching. The principle of operation of the electro-optic modulator which I am developing is based on the quadratic electro-optic effect (Kerr Effect) in a KLTN crystal operating at the paraelectric phase. The Optical properties of the crystal change when electromagnetic voltage is applied to the crystal. By using two crossed polarizers we are able to control the intensity of the light emitted from the modulator. The electro-optic modulator provides high modulation frequencies and the ability to use high light intensities. My main challenges in this project were as follows: (1) Minimizing light intensity losses - the main component of the system - the crystal has a refractive index of 2.2. This yielded inherent loss of approximately 30%; (2) Reaching high switching frequencies - in order to achieve narrow and frequent pulses we must achieve a fast control of the voltage applied on the crystal. I addressed these challenges by: (1) Developing an anti-reflective layer for the crystal in order to reduce losses; (2) Characterizing the crystals in order to choose the most suitable sample and selecting the optimal working point; (3) Designing a fast electronic system in order to reach high switching frequencies.

Project memberZaharit Itin-Refaeli zaharit.itin@mail.huji.ac.il

SupervisorsProf. Aharon J. Agranat, The Hebrew University of JerusalemMr. Noam Meyuhas, The Hebrew University of Jerusalem

Can we make phone conversations as actionable as textual communications? Many users neglect to follow-up on topics that come up in their phone conversations. We therefore propose a mobile app that suggests targeted actions to the user based on phrases and topics mentioned in his recent phone conversation and contextual information capturing repeating user behaviors.For example, after a phone conversation with a friend asking you to order pizza for the party this evening, our system would provide a “Chlli’s Pizza” order notice. Alternatively, if the friend mentions the address, you will no longer need to write it down but rather rely on our system to provide a “navigate to” card at the end of the call.The system relies on a machine learning cycle, supervised by implicit user-feedback. Using this approach the app gradually learns what actions are most effective in helping the user follow-up on his phone calls.

Project membersTamir Tiomkin tamir.tiomkin@mail.huji.ac.ilDaniel Zateikin daniel.zateikin@mail.huji.ac.il

SupervisorDr. Michael Fink, Google Inc

Recommending Actions Based on Phone Conversations

8 | | 7

Metal DetectorOur project comes to fill the gap in the metal detection field, in which there is no easy to use, qualitative, cheap & available product.Although our product is needed in several industries, such as the building industry, food industry, Army etc., in our project we focus on the building industry, since we found that this is the field where we can make the biggest improvement, and we realized that providing a solution to this field will, implicitly, provide a solution to all fields.Our product contains a scanning device, in which we implemented an electric circuit, which after scanning a wall transforms the data to our Android app, via an Arduino board and Bluetooth. Through this, the end user gets an indication of existence of metal in the scanned area.The main advantage in our product in the exploitation of the advanced processing ability of the user’s smartphone, with the assumption that in today’s market everyone has a smartphone. This is a great feature that makes our product qualitative, not expensive, and thus very valuable.

Project MembersTal Dovrat taldovrat1988@gmail.comOren Ben-Meir orenbm21@gmail.com

SupervisorDr. Amir Ben-Shalom, Bloomfield Science Museum

Real Time Flash-Flood Warning System Flash-flood warning models can save lives and protect various kinds of infrastructure. In dry climate regions, rainfall is highly variable and can be of high-intensity. Since rain gauge networks in such areas are sparse, rainfall information derived from weather radar systems can provide useful input for flash-flood models. Our project is based on a scientific paper, which describes an offline model for predicting a flash-flood in the Dead Sea area. Our goal was to learn the model and create a new system which utilizes the basics of the offline model, as described in the paper, in order to create a dynamic, real time system that receives the radar data and produce up to date and rapid warnings for near future flash-floods in the region.The new system is based on three main modules. The first module handles the dynamic update of the state of the soil in the area and computes the local runoff according to high resolution radar images of rainfall in the region, with an interval of one minute per picture. The last two modules are in charge of runoff transportation over the catchment, where each module is in charge on a different area type – hillslopes and channels. The system monitors and updates the state of the soil and computes runoff, which is being updated rapidly by the first module, and by use of predefined parameters it decides if a prediction should be done. The last two modules transport the runoff over the hillslopes and through the channel network in order to produce a prediction, which in the end will create a flash flood warning if the computed discharge is more than the predefined warning threshold.

Project membersOded Valtzer oded.valtzer@mail.huji.ac.ilItzhak Oskovski itzhak.oskovski@mail.huji.ac.il

SupervisorProf. Efrat Morin, The Hebrew University of Jerusalem

10 | | 9

Search Engine from an Image SequenceJustVisual provides an API for visual search in various domains: pets, home décor, fashion, flowers, food and more. The company has also released its own applications based on this API, branded as "LikeThat".The "LikeThat" applications are well known for their accurate results. Nevertheless, there is a lack of performance when the taken photo is not "at its best". For example, when the user moves while taking the photo (very common) or when the object moves while the photo is taken. Another problem is that sometimes object results are different from one shot to another (while taking photos of the same object).Our project aims to fix these problems by taking a very short video (a sequence of images) instead of one shot (without even letting the user know). Using machine learning methods, we choose the most successful frames for our purpose out of this video and execute the search engine on them.Then, by additional machine learning tools, we manage to pick the best results, and provide them to the user in real-time, along with confidence signal which we developed.We focused on womens' clothing object (which is obviously a quite difficult object), but the principles and ideas of the algorithm can be easily applied to any other object.

Project membersOfir Yagil ofir.yagil@mail.huji.ac.ilNir Keisar nir.keisar@mail.huji.ac.il

SupervisorMr. Michael Chertok, JustVisual

Image Background Suppression from Hand Jitter on Mobile PhonesIn order to perform visual searches and image recognition, one must use images containing the object of interest. Due to the fact the background is sometimes a significant part of the image, the search and recognition results may rely heavily on the background. This means that images of the same object, with different backgrounds, achieve different, and sometimes poor results.The goal of our project is to suppress the background of the image and separate the object from the background, so the background won't affect the results.The algorithm we developed takes advantage of the user's hand jitter to capture a sequence of images of the object, and uses those images in combination with data from the phone sensors to create a depth map of the scene. The depth map is then used to distinguish the selected object from the background by distance from the camera. The approaches tested included various optical flow algorithms and segmentation algorithms.Our main challenge was dealing with images in which the object of interest was approximately the same distance from the camera as other objects in the image, causing these objects to be considered as foreground as well.

Project membersGilad Bar gilad.bar1@mail.huji.ac.ilDan Schwarzzman dan.schwarzzman@mail.huji.ac.il

SupervisorMr. Michael Chertok, Co-Founder & CTO at JustVisual

12 | | 11

Time-Correlated Single Photon Counting (TCSPC) System, Used for Measuring Excitonic Life-Time of Nano-StructuresNanotechnology is changing the world, creating scientific advances and new products that are smaller, faster, stronger, safer, and more reliable in a broad range of fields such as electronics, biology, medicine, security etc. Therefore, it is crucial to obtain knowledge about the physics of nano-scale structures, which is dominated by quantum mechanics rules. Photoluminescence (PL) is light emission from any form of matter after the absorption of light. The absorption of light triggers processes that are specific and local to each material and which are affecting the time it takes for the light to be emitted (lifetime), and the exact emitted wavelength (the color of the emitted light). Therefore, sensitive relaxation measurements allow the characterization of a variety of physical properties in the nanometric-scale. For example, a high resolution lifetime measurement is a key indicator for quantum phenomena such as energy and charge transfer within the nano-structure.The aim of my project is to construct a high resolution measurement system in order to study nano-metric quantum processes. More specifically, I have developed an optical, picosecond (ps)-resolution excitonic lifetime measurement system. Naively, measurement of the lifetime decay requires fast detection of photons with temporal resolution of ~10ps, which would be impossible to achieve by standard electronics and detectors. Therefore, a method called Time-Correlated Single Photon Counting (TCSPC) is used.The method is based on a repetitive and precisely timed registration of single photons from a fluorescence signal (using a sensitive detector). Excitation driven fluorescence is repetitively generated using short laser pulses, and the time difference between excitation and emission is measured by electronics that act like a stopwatch. The stopwatch readings are sorted into a histogram consisting of a range of “time bins”. The reconstruction of the fluorescence decay profile is done using a multitude of single photon events, collected over many cycles.The uniqueness of my system lies mainly on its ~50ps temporal resolution (compared to ~200ps temporal resolution, commercially available systems), achieved using state of the art components along with a custom-made data analysis program that calculates the de-convolution between the measurement and the system’s instrument response function (IRF). The system is also characterized by various optional excitation wavelengths (400-700nm), repetition rates (100kHz - 40MHz), and light polarizations (non\linear\circular), And it is built out of flexible different modules that can be operated separately.

Project MemberLior Bezen lior.bezen@mail.huji.ac.il

SupervisorProf. Yossi Paltiel, The Hebrew University of Jerusalem

Auto Fly – Autonomous Drone HomingNowadays, drones use GPS, remote control or preflight plan in order to get to a desired location. Previous drones built by various companies were expensive projects (e.g. Amazon, Australia Post).In our project, we built a low budget autonomous drone that is able to close in on a target using computer vision and machine learning techniques.To do this, we installed an Odroid computer chip, Gimbal, and a webcam. Our algorithm iteratively receives pictures from the webcam and checks if the target is in them. If the target is found, the algorithm locates it and flies the copter toward that direction. One of the main challenges we faced during the project was applying our methods using a low budget. We had to take many measures to overcome the disadvantages and weaknesses of those systems. For example, we used sophisticated algorithms to compensate for technical lack of accuracy in the drone’s position holding.

Project membersLeshem Choshen leshem.choshen@mail.huji.ac.ilGuy Hacohen guy.hacohen@mail.huji.ac.il

SupervisorsMr. Refael Vivanti, Rafael Advanced Defense SystemsProf. Michael Werman, The Hebrew University of Jerusalem

14 | | 13

Haptic Vision - Indoor Navigator for the BlindWorldwide there are an estimated 300-400 million individuals who are blind and visually impaired. Accessibility has long been a big technological challenge for humanity in trying to help disabled populations. Prof. Amir Amedi's lab, located in Hadassah Ein Kerem, is actively researching the field of multisensory integration (i.e, vision as well as other senses) and applies its findings to develop Sensory Substitution Devices (SSD) for the visually impaired community.One of the main problems effecting the blind community is the inability to navigate autonomously outdoors and indoors. The most common solutions used today are a white cane and a guide dog. Unfortunately, a cane is often clumsy and a dog could get tired and loose its way in new surroundings, both are highly noticeable and can cause a person to feel uncomfortable.In our project we decided to focus on finding a proper solution for blind navigation indoors. Our goal is to ease the navigational difficulty for a visually impaired user by creating a device that will be easy to use and won't be noticeable.To achieve this, we developed an algorithm that receives as an input a real-time image from a mobile phone camera and determines the center of the corridor. Using this information, the algorithm then calculates the estimated lateral distance between the user and the corridor center; it is then used to evaluate the required corrective movement the user needs to take.This information is passed through a Bluetooth transmitter to a micro-controller that runs two vibration motors located on each of the user’s shoulders.These vibrations direct the user to the center of the corridor by operating with different intensities on the shoulder closer to the center (opposite the false trajectory), with a stronger vibration indicating a bigger distance. Project membersAdi Tanami adi.tanami@mail.huji.ac.ilVladi Kravtsov vladi.kravtsov@mail.huji.ac.i

SupervisorsProf. Amir Amedi, lab team leader of Amir Amedi’s lab, Hadassah Ein KeremMr. Or Yizhar, Amir Amedi’s lab, Hadassah Ein Kerem

Classification of Malicious Files into Families Using Machine Learning Based on Features of the Binary FileClassification of malicious software (malware) is a fundamental problem in cyber security, since we want to know what is inside the file before it gets into the system. Therefore, it is important to recognize the structure of malicious files, in order to avoid them and create a proper response. Our system receives as input a binary stream – there is no need for metadata or other information. Our challenge was to understand the features and file structure that each malware class share in common, and find them in binary sequences. Our solution uses Machine Learning methods to learn the code structure and trains a model using a high volume of labeled data. Then it can predict the content of new files.This ability is very useful for malware classification, and that is how we test our framework.The framework splits the binary code to small chunks, analyzes each one of them using feature extraction methods and presents them to a Machine Learning model, which can give us a prediction for further analysis.We applied our system to a high volume dataset of labeled malware, which we analyzed according to our feature extraction scheme, and validated that it is capable of assigning a correct family to malware samples.

Project membersYishay Merzbach Yishay.Merzbach@mail.huji.ac.ilJonathan Giber Jonathan.Giber@mail.huji.ac.il

SupervisorsMr. Tomer Brand, Microsoft Dr. Shay Kels, Microsoft

16 | | 15

Rapid Optical Sensing of Bacteria Using Porous Silicon Photonic Phase GratingsBacterial germs are all around us - one crucial aspect of food quality assurance is sensing these ubiquitous bacteria in order to assure quality healthy food. The available methods of bacterial detection nowadays are slow, old fashioned and not reliable enough. A simple, rapid, portable and inexpensive solution would, consequently, be a highly valuable contribution to the food industry.The goal of this project is to build a system capable of sensing low concentrations of bacteria in fluids within a few minutes, meeting the industry requirements and standards.The main mechanism of the proposed system involves streaming of the examined fluid upon a porous silicon chip. Light reflected from the surface of the silicon chip is then analyzed, enabling us to detect small changes in the refractive index and thereby sensing the presence of bacteria. The structure of the silicon chip ensures that we will be able to trap bacteria and not larger particles. The light analysis is based on RIFTS (Reflective Interferometric Fourier Transform Spectroscopy).Two main challenges had to be dealt with during the project. First, optimization of the optical signal acquisition in order to increase the sensitivity of the system. Second, understanding the dynamics of bacterial sensing – a constantly evolving and changing system.The system was proven to be an effective, easy to use and a potential alternative to current techniques used in the industry.

Project membersYaniv Padé yaniv.pade@mail.huji.ac.ilEilon Maydan eilon.maydan@mail.huji.ac.il

SupervisorProf. Amir Sa’ar, The Hebrew University of Jerusalem

Scene Segmentation & Simplification for Sensory SubstitutionOne of the main methods to assist blind and visually impaired individuals is to use sensory substitution devices (SSDs), such as the EyeMusic visual-to-auditory SSD, which conveys visual information via audition. Shapes, location and color are converted into sound thus enabling its users to understand their visual surroundings.The main impediment of adopting such approaches lies in the long training period required to fully use such devices in the noisy `real' world, which differs from its simplified use in the lab.For simplifying the EyeMusic real-world input, we have created and embedded two modules within the EyeMusic application– one is responsible for detecting objects (currently faces and full bodies) and enables the user to estimate the object's location and distance. The second simplifies each image by reducing its palette and enabling a cartoon-like view. These modules can be used separately and together, according to users' choice. Potentially these features will provide users with an understanding of the "visual" world in a beneficial manner, while decreasing the training duration.

Project membersDanny Boguslavsky danny.boguslavsky@mail.huji.ac.ilDavid Gefen david.gefen1@mail.huji.ac.il

SupervisorsProf. Amir Amedi, The Hebrew University of JerusalemProf. Leo Joskowicz, The Hebrew University of JerusalemMs. Galit Buchs, The Hebrew University of Jerusalem

18 | | 17

Smartphone Physics LabIt is quite surprising that, in a world where every high school student or teacher carries sensor-laden smartphones in their pockets, classroom physics experiments are still conducted with antiquated, boring and imprecise equipment or, alternatively, with expensive custom-made equipment. Why not have students learn physics in an interactive and interesting way, by utilizing an instrument which already accompanies them and is at their disposal all day long…Our project is designed to help teach physics in a simple yet interesting fashion, by allowing students to perform classic lab experiments through a plain and friendly smartphone-based interface. The app lets you perform each and every stage of the experiment, from taking the initial measurements to processing the data and calculating the results, with virtually no need for any additional accessories or equipment. Rather than being confined to the school laboratory, it can be used anywhere.While there are alternative solutions, such as the “Einstein” Tablet, these require the use (and purchase) of (relatively expensive) designated equipment. There is also a variety of apps which enable the use of the smartphone as a measuring device or as an electronic data processing chart, but the majority of these are not designed or suitable for conducting physics lab experiments. The app we developed utilizes the smartphone’s built-in sensors in order to perform measurements, its computational capacity in order to process and present data and makes use of its other features, in order to improve measurement accuracy.

Project membersAdi Ohana adi.ohana@mail.huji.ac.ilDavid Freud david.freud@mail.huji.ac.il

SupervisorDr. Amir Ben Shalom, Bloomfield Science Museum

Global Multiview Image - Color Correction for Seamless 3D ReconstructionIn a multiple-view image acquisition process, color consistency is not ensured due to: the automatic camera settings, different surface orientations in relation to the camera and light source and shading. This is an important consideration for image fusion, object texturing or mosaic blending.Our project offers a global multi-view solution with recovered consistent color textures for each image - without illumination impact or shading artifacts.Removing illumination effects from each image was done by modeling the sky and sun illuminations according to estimated sky turbidity, sun location and sun intensity.This solution produces a 3D model that is seamless and photorealistic, which can be illustrated with varied illumination conditions (sunrise, sunset etc.).

Project membersLior Moshe lior.moshe1@mail.huji.ac.ilCarmel Einhorn carmel.einhorn@mail.huji.ac.il

SupervisorsMr. Avram Golbert, Rafael Ltd.Prof. Dani Lischinski, The Hebrew University of Jerusalem

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Cheap Magnetic System for Underground MappingMagnetic mapping is an effective way to locate underground objects made of iron or other ferromagnetic materials. It is usually done by moving a sensor over an area and measuring the magnetic magnitude at each point. Existing mapping systems are very expensive because they are based on an atomic scalar magnetic sensor. Our system solves this problem, by using a 3-axes vector flux-gate magnetic sensor. This sensor is very cheap, but suffers from critical problems of inaccuracy when in motion. Therefore, it was impossible to use this kind of sensor for mapping purposes. We developed an efficient calibration technique, which solves this problem by applying a correction transformation on the sensor’s raw data. As a result, the cheap sensor can now accurately measure magnitude at all orientations. In addition, we found the best hardware configuration to turn an inaccurate vector sensor into an accurate scalar mapping system. The system was tested in many experiments, which proved its mapping capability. In addition, we developed a friendly graphical user interface, which makes the calibration and the mapping process very fast and intuitive.

Project membersAlon Shavit Alon.shavit@mail.huji.ac.ilGal Zadock Gal.zadock@mail.huji.ac.il

SupervisorDr. Eyal Weiss, Soreq Nuclear Research CenterISM Band Analysis and Ranging

The ISM (Industry, Science and Medical) frequency bands are non-regulated RF bands for general purpose uses; they owe their existence to radio enthusiasts and now enable widespread usages from Wifi and Bluetooth connections to garage remote controls.To allow so many diverse applications to operate in a non-regulated medium, the ISM standard dictates transmission limitations (bandwidth, power and duration). But what happens when someone violates these limitations?The goal of this project is to produce a system that will monitor the RF usage in a specific locale over time, help to visually analyze the results and finally provide operators with ranging capabilities to physically locate the transgressors.Our major challenge was the realities of working with microprocessors and radio components, e.g. allowing components to settle before sampling or handling data loss due to power saving stand-by.

Project membersJonathan Hirsch jonathan.hirsch@mail.huji.ac.ilLior Barak lior.barak1@mail.huji.ac.il

SupervisorMr. David Benita

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Extracting, Classifying and Optimizing Loops in a Binary CodeMost of the code we usually run on our personal computers is in the form of an executable file. This means we can never be sure that the code that is being run is truly trustworthy since the source code is not available to us. In the field of malicious software, the programs disguise themselves as innocent programs that you would normally need, while hiding harmful code within in them. This code is intended to exploit your system with several techniques such as the Trojan horse. One of the main aspects of detecting such malicious code, is through the structure of the loops inside.Our goal in this project is to detect, extract, classify and analyze loops in the binary code. After disassembling the binary code, using a machine learning algorithm we managed to classify each detected loop into six specific classes. For the next step we used REIL (Reverse Engineering Intermediate Language) in order create a flow graph of the loop, then calculated the exit criteria using a SMT solver.

Project membersShai Hoffman shai.hoffman@mail.huji.ac.ilYarden Oren yarden.oren@mail.huji.ac.il

SupervisorMr. Tomer Brand, Microsoft

Smart SearchSearch engines are widely used in our world today, but the method of search as well as the results may not be very intuitive.Our project aims to change that by changing the way in which the search results are presented to us.We gather the results of a search query and using language processing methods, we find the variety of topics that comprise those results. We then visualize the categories in a clear and intuitive map and present the results in a way that makes narrowing the search both user friendly and immediate, making searching and exploring the web fun and interactive.

Project membersAmichai Horvitz amichai.horvitz@mail.huji.ac.ilFeras Ghanim feras.ghanim@mail.huji.ac.il

SupervisorMr. Effi Levi, The Hebrew University of Jerusalem

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Low Resource Image labeling with Application for Mobile DevicesObject recognition in images is a well-known problem. Currently it is a big part of the Deep CNN revolution, being implemented on high end computers while running on dedicated GPUs.The aim of this project is to find low resource algorithms capable of classifying a smaller amount of classes (~20) while running on low resource devices such as smartphones.In our project we used a convolutional neural network (CNN) which we trained on 20 classes using imagenet data collection. Convolutional neural network makes a great amount of mathematical calculations which requires high end computers to get results in reasonable runtime.Our main challenge was to reduce the runtime and storage needed for our network while still get good recognition results. In order to achieve this we reduced the size of the network (number of neurons) using a pruning algorithm that kept only the important neurons.Our final product is an application which recognizes an object shown to the camera of the phone and writes the object description.

Project membersShachar Swissa dawn.swissa@huji.ac.ilDan Almog dan.almog@mail.huji.ac.il

SupervisorMr. Ofir Bibi, Lightricks

Drinking Water indicatorThe high cost of equipment for monitoring water quality often puts valuable health tools out of reach for many communities in developing countries. Consequently, millions of people are exposed to health risks that could be mitigated if solutions were available at a price which they can afford.Turbidity refers to the dirtiness or cloudiness of a water sample, and an internationally recognized criterion for assessing drinking water quality because the colloidal particles in turbid water may harbor pathogens, chemically reduce oxidizing disinfectants, and hinder attempts to disinfect water with ultraviolet radiation. The Israeli Health Organization allows drinking water to have turbidity concentration of below 1NTU (unit), which isn’t visible to the human eye.Water chlorination is the process of adding chlorine (Cl2) or hypochlorite to water. Chlorination is used to prevent the spread of waterborne diseases. Chlorine is highly toxic, so it is present in most disinfected drinking water at very low (< 1mg/L) concentrations.The goal of my project is to create a low-cost device to measure the turbidity and chlorine level of a water supply. This device is optically based and works in a manner very similar to the human eye. It is accurate enough to indicate either the tested water is drinkable or not, and measures both turbidity and chlorine in a high resolution. The results are displayed on a web based interface and stored on the cloud for further analysis.

Project memberIsaac Delarosa isaac.delarosa@mail.huji.ac.il

SupervisorProf. Nissim Ben-Yossef, The Hebrew University of University

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21 Cheap Magnetic System for Underground Mapping Alon Shavit Gal Zadock

26 Drinking water indicator Isaac Delarosa

7 Electro-Optic Modulation and Switching at 2μ Wavelengths Zaharit Itin-Refaeli

17 Rapid Optical Sensing of Bacteria Using Porous Silicon Photonic Phase Gratings Yaniv Padé Eilon Maydan

13 Time-Correlated Single Photon Counting (TCSPC) System, Used for Measuring Excitonic Life-Time of Nano-Structures Lior Bezen

Electrical & Computer EngineeringSpecializing in Microelectronics and Optoelectronics

Electrical & Computer EngineeringSpecializing in Computer Engineering

PROJECT DIRECTORyPROJECT DIRECTORy

5 Audio-Visual Speech Enhancement Using Deep Learning Moshe Mandel Nofar Noy

14 Auto Fly – Autonomous Drone Homing Leshem Choshen Guy Hacohen

16 Classification of Malicious Files into Families using Machine Learning Based on Features of the Binary File Yishay Merzbach Jonathan Giber

24 Extracting, Classifying and Optimizing Loops in a Binary Code Shai Hoffman Yarden Oren

19 Global Multiview Image - Color Correction for Seamless 3D Reconstruction Lior Moshe Carmel Einhorn

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15 Haptic Vision - Indoor Navigator for the Blind Adi Tanami Vladi Kravtsov

12 Image Background Suppression from Hand Jitter on Mobile Phones Gilad Bar Dan Schwarzzman

6 Intuitive Real Time Music Developer Neria Saada Issack Rosenberg

22 ISM Band Analysis and Ranging Jonathan Hirsch Lior Barak

25 Low resource Image labeling With Application for Mobile Devices Shachar Swissa Dan Almog

9 Metal Detector Tal Dovrat Oren Ben-Meir

10 Real-Time Flash-Flood Warning System Oded Valtzer Itzhak Oskovski

PROJECT DIRECTORyPROJECT DIRECTORy

Electrical & Computer EngineeringSpecializing in Computer Engineering

Electrical & Computer EngineeringSpecializing in Computer Engineering

3 Real-Time Mobile Based Gaze Tracking Chayim Ehrman Zeev Adelman

8 Recommending Actions Based on Phone Conversations Tamir Tiomkin Daniel Zateikin

18 Scene Segmentation & Simplification for Sensory Substitution Danny Boguslavsky David Gefen

11 Search Engine from an Image Sequence Ofir Yagil Nir Keisar

20 Smartphone Physics Lab Adi Ohana David Freud

23 Smart Search Amichai Horvitz Feras Ghanim

4 Voice Modification Yehuda Babayof Boris Talesnik

Faculty of Mathematics and ScienceThe Rachel and Selim Benin School of Engineering and Computer Science

Final Projects presentation of the

14th Graduating ClassElectrical & Computer EngineeringProgramsand awards ofthe Peter Brojde Center for InnovativeEngineering and Computer Science

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