Empirical model-based control for end milling process

The main objective of this research is to develop an empirical model-based control mechanism to maintain a fine surface finish quality by maintaining on-line cutting force values. The proposed model has been developed to present the control model constraints, by varying the machining parameters to control the force output to be constant. To relate the surface finish and the cutting force in the end milling machining process, a design of experiment has been conducted to determine the effect of two different materials (aluminium and steel) and the machining parameters (feed rate, spindle speed) at a predefined depth of cut. Regression model has been applied to derive an empirical relationship of the surface finish and the cutting force versus the machining parameters for the two mentioned materials. These relationships have been applied to develop the proposed mathematical simulation model, in which the cutting force is adjusted to improve the required surface finish for the end milling operation process. The results provide means of greater efficiency by improving the surface quality, minimizing the effect of the process variablity and reducing the error cost in finishing operations

Deep learning for quantitative motion tracking based on optical coherence tomography

Optical coherence tomography (OCT) is a cross-sectional imaging modality based on low coherence light interferometry. OCT has been widely used in diagnostic ophthalmology and has found applications in other biomedical fields such as cancer detection and surgical guidance. In the Laboratory of Biophotonics Imaging and Sensing at New Jersey Institute of Technology, we developed a unique needle OCT imager based on a single fiber probe for breast cancer imaging. The needle OCT imager with sub-millimeter diameter can be inserted into tissue for minimally invasive in situ breast imaging. OCT imaging provides spatial resolution similar to histology and has the potential to become a device to perform virtual biopsy to fast and accurate breast cancer diagnosis, because abnormal breast tissue and normal breast tissue have different characteristics in OCT image. The morphological features of OCT image are related to the microscopic structure of the tissue and the speckle pattern in OCT image is related to cellular/subcellular optical properties of the tissue. In addition, depth attenuation of OCT signal depends on the scattering and absorption properties of the tissue. However, the above described OCT image features are at different spatial scales and it is challenging for human visualization to effectively recognize these features for tissue classification. Particularly, our needle OCT imager, given its simplicity and small form factor, does not have a mechanical scanner for beam steering and relies on manual scan to generate 2D images. The nonconstant translation speed of the probe in manual scanning inevitably introduces distortion artifacts in OCT imaging, which further complicates the tissue characterization task.] OCT images of tissue samples provide comprehensive information about the morphology of normal and unhealthy tissue. Image analysis of tissue morphology can help cancer researchers develop a better understanding of cancer biology. Classification of tissue images and recovering distorted OCT images are two common tasks in tissue image analysis. In this master thesis project, a novel deep learning approach is investigated to extract beam scanning speed from different samples. Furthermore, a novel technique is investigated and tested to recover distorted OCT images. The long-term goal of this study is to achieve robust tissue classification for breast cancer diagnosis, based on a simple single fiber OCT instrument. The deep learning network utilized in this study depends on Convolutional Neural Network (CNN) and Naïve Bayes Classifier. For image retrieval, we used algorithms that extract, represent and match common features between images. The CNN network achieved accuracy of 97% in tissue type and scanning speed classification, while the image retrieval algorithms achieved very high-quality recovered image compared to the reference image

Using a Learner-Centered Approach to Develop an Educational Technology Course

The article explores the structure of a graduate educational technology course that used a learner-centered approach to prepare students to be independent responsible learners. Key features of this approach were the balance of power between the instructor and students, involving students in decision-making about their learning, sharing the responsibility for learning between the instructor and students, and using students\u27 needs and interests in the course content. The article describes how the decision-making power was shared between the instructor and students, as well as how students responded to the course structure. This work has implications for creating learner-centered environments in which power and responsibility are shared between instructor and students in all graduate education courses to nurture the development of responsible learners

How to merge courses via Skype™†? Lessons from an International Blended Learning Project‡

This study reports on an international project in which students taking the course Contemporary Issues in Turkish Politics in spring 2011 and fall 2011 at two institutions of higher education, ‘Gettysburg College’ in the United States and ‘Izmir University of Economics’ in Turkey, worked together in virtual learning environments to complete various tasks as part of their course work. The project employed a blend of traditional and technology-based teaching methods in order to introduce a technology like Skype in a bi-national learning environment in Turkey. Students collaborated and interacted with their international counterparts in two different virtual contexts. First, classrooms in the two countries were merged via Skype three times to conduct classroom-to-classroom discussion sessions on Turkish politics. Second, students were paired across locations to work on several assignments. In this paper, our goal is to present how Skype is used in a bi-national context as a blended teaching tool in an upper-level college course for instructors pursuing a similar exercise. In addition to outlining the process with a focus on Skype discussions and one-on-one student projects, we provide actual assignments and discussion questions. Students’ views elicited through surveys administered throughout the semester are presented alongside anecdotal evidence to reflect how the project was received

MXenes: A New Family of Two-Dimensional Materials and its Application as Electrodes for Li-ion Batteries

Two-dimensional, 2D, materials, such as graphene, possess a unique morphology compared to their 3D counterparts, from which interesting and novel properties arise. Currently, the number of non-oxide materials that have been exfoliated is limited to two fairly small groups, viz. hexagonal, van der Waals bonded structures (e.g. graphene and BN) and layered transition metal chalcogenides. The MAX phases are a well established family of layered ternary transition metal carbides and/or nitrides, with a composition of Mn+1AXn, where M is an early transition metal, A is one of A group elements, X is C and/or N; with n = 1, 2, or 3. The aim of this work is to exfoliate the MAX phases and produce 2D layers of transition metals carbides and/or nitrides by the selective etching of the A layers from the MAX phases. We labeled the resulting 2D Mn+1Xn layers "MXenes" to emphasize the loss of the A group element from the MAX phases and the suffix "ene" to emphasize their 2D nature and their similarity to graphene. The etching process was carried out using aqueous hydrofluoric acid at room temperature. Thirteen different MXenes were produced as a result of this work, viz., Ti2C, Nb2C, V2C, Mo2C, (Ti0.5,Nb0.5)2C, (Ti0.5,V0.5)2C, Ti3C2, (Ti0.5,V0.5)3C2, (V0.5,Cr0.5)3C2, Ti3CN, Ta4C3, Nb4C3 and (Nb0.5,V0.5)4C3. The as-synthesized MXenes were terminated with a mixture of OH, O, and/or F groups. Sonicating MXenes resulted in separating the stacked layers to a small extent. When Ti3C2 was intercalated with dimethylsulfoxide, however, followed by sonication in water, large-scale delamination occurred, which resulted in aqueous colloidal solutions that could in turn be fabricated into MXene "paper". MXenes were found to be electrically conductive, hydrophilic and stable in aqueous environments, a rare combination indeed, with huge potential in many applications, from energy storage, to sensors to catalysts. This work focused on the use of MXenes as electrode materials in Li-ion batteries. They exhibited excellent capability to handle high cycling rates with good gravimetric capacities. The lithiation and delithiation were found to be due to redox intercalation/deintercalation reactions.Ph.D., Materials Science and Engineering -- Drexel University, 201

Cyber-Physical Power System Layers: Classification, Characterization, and Interactions

This paper provides a strategy to identify layers and sub-layers of cyber-physical power systems (CPPS) and characterize their inter- and intra-actions. The physical layer usually consists of the power grid and protection devices whereas the cyber layer consists of communication, and computation and control components. Combining components of the cyber layer in one layer complicates the process of modeling intra-actions because each component has different failure modes. On the other hand, dividing the cyber layers into a large number of sub-layers may unnecessarily increase the number of system states and increase the computational burden. In this paper, we classify system layers based on their common, coupled, and shared functions. Also, interactions between the classified layers are identified, characterized, and clustered based on their impact on the system. Furthermore, based on the overall function of each layer and types of its components, intra-actions within layers are characterized. The strategies developed in this paper for comprehensive classification of system layers and characterization of their inter- and intra-actions contribute toward the goal of accurate and detailed modeling of state transition and failure and attack propagation in CPPS, which can be used for various reliability assessment studies.Comment: Accepted in Texas Power and Energy Conference (TPEC) 202