Intellectual Property Valuation Using Income Approach Method for Technology Licensing

Technology licensing is one of the key transactions that enable translation of R&D investments into profits by commercialization of technology. The elementary economics of such transaction suggests that while a licensor attempts to derive benefits greater than the cost of development of the technology protected by IPR, in exchange of monopoly rights, the licensee attempts to minimize the license value to ensure higher profits. This leads to the requirement of valuation of the technology by either party. This paper presents some of the key characteristics related to intellectual property valuation and an analysis of the income method approach in estimating the profitability of commercialization of a technology involving a patent

The Evolution of Public Health and Current Challenges: A Review

From the ancient ages, the human has been plagued by numerous diseases. While ancient people attributed disease due to divine causation and was stigmatised or isolate from the society, the middle ages let scientists find a reasonable explanation for disease, which led to discoveries of microorganisms and maintaining a clean environment and thus, Public Health Was born. This review discusses the evolution of Public Health and current challenges faced by Public Health Professionals

Garbage collection schemeoptimization in YAFFS

In this project we present an improved garbage collection scheme for YAFFS2 (Yet Another Flash File System). Our objective was to reduce the number of Aggressive Garbage Collections in Garbage Collection module of YAFFS2. We explore the various values of beta (ratio of number of erased chunks to number of free chunks) experimentally and try to find the optimal value of beta for which number of Aggressive Garbage Collections (Garbage Collection) is the least. Extensive tests were conducted by varying the value of beta (0< beta<1). A total of three tests were used to determine the number of Garbage Collections in different scenarios: a write test (clean write as well as overwrites), an erase test and a post erase test Garbage Collection monitoring test. A generic write test and an erase test were provided with YAFFS2 source code, which needed little modifications. The last test was developed by us as the situation demanded. Reduction in the number of Aggressive Garbage Collections reduces computational load on the processor, which in turn saves power, especially in battery powered devices

Identifying KIF Subtype that Mediates Axonal Targeting of Kv7 Channels

Early-onset Benign Familial Neonatal Epilepsy (BFNE) and Epileptic Encephalopathy (EE), are associated with mutations in neuronal KCNQ/Kv7 channel subunits Kv7.2 and Kv7.3. Kv7 channels are voltage-dependent potassium channels. Enriched at the axonal plasma membrane, they pump potassium ions out of the neurons and inhibit repetitive or burst firing of action potentials. A single neuronal Kv7 channel is a heterotetramer composed of two Kv7.2 and two Kv7.3 subunits. BFNE and EE mutations in Kv7.2 and Kv7.3 lead to decreased surface expression along the axon, which means less potassium ions are moved across the axonal membrane where action potentials are generated and propagated. This prevents the neuron from returning to its resting potential and allows repetitive action potentials indicative of a seizure. The purpose of this project is to uncover the molecular mechanism by which Kv7 channels are targeted to the axonal surface and enriched at the axonal initial segment (AIS). Since epilepsy mutations in Kv7 channels reduce this axonal targeting, understanding the mechanism underlying axonal targeting could provide therapeutic targets to treat epilepsy. Two motor proteins KIF3A and KIF5B are shown to target other potassium channels such as Kv1 to the axon. Here, we are investigating to test if overexpression of KIF3A and KIF5B proteins will lead to increased surface expression of neuronal Kv7 channels in the axon of hippocampal neurons

A Prototype Model to Improve Bandwidth of E Shaped Microstrip Patch Antenna

In this communication we have demonstrate a prototype model to improvise bandwidth of E shaped microstrip patch antenna. Microstrip patch antenna is widely used in wireless communication system. Patch antenna has number of advantage over other antenna. It is low volume, thin profile configuration, light weight and easy to integrate with accompanying electronics which can made conformal but, Microstrip patch antenna has several limitations like narrow bandwidth and associated tolerance problem, lower gain. Patch antenna can be designed on simulation software like HFSS. This paper present Design and simulation of E shaped microstrip patch antenna and analyzed result Bandwidth, Gain, Return loss etc has been presented.Derived results show that E shaped Patch antenna is better for the improvement of Bandwidth of the antenna

Machine Vision Using Cellphone Camera: A Comparison of deep networks for classifying three challenging denominations of Indian Coins

Indian currency coins come in a variety of denominations. Off all the varieties Rs.1, RS.2, and Rs.5 have similar diameters. Majority of the coin styles in market circulation for denominations of Rs.1 and Rs.2 coins are nearly the same except for numerals on its reverse side. If a coin is resting on its obverse side, the correct denomination is not distinguishable by humans. Therefore, it was hypothesized that a digital image of a coin resting on its either size could be classified into its correct denomination by training a deep neural network model. The digital images were generated by using cheap cell phone cameras. To find the most suitable deep neural network architecture, four were selected based on the preliminary analysis carried out for comparison. The results confirm that two of the four deep neural network models can classify the correct denomination from either side of a coin with an accuracy of 97%.Comment: 6 Pages, 4 Figures, 6 Tables, Conference pape

ChatGPT -- a Blessing or a Curse for Undergraduate Computer Science Students and Instructors?

ChatGPT is an AI language model developed by OpenAI that can understand and generate human-like text. It can be used for a variety of use cases such as language generation, question answering, text summarization, chatbot development, language translation, sentiment analysis, content creation, personalization, text completion, and storytelling. While ChatGPT has garnered significant positive attention, it has also generated a sense of apprehension and uncertainty in academic circles. There is concern that students may leverage ChatGPT to complete take-home assignments and exams and obtain favorable grades without genuinely acquiring knowledge. This paper adopts a quantitative approach to demonstrate ChatGPT's high degree of unreliability in answering a diverse range of questions pertaining to topics in undergraduate computer science. Our analysis shows that students may risk self-sabotage by blindly depending on ChatGPT to complete assignments and exams. We build upon this analysis to provide constructive recommendations to both students and instructors.Comment: This is a work in progres

Speakerly: A Voice-based Writing Assistant for Text Composition

We present Speakerly, a new real-time voice-based writing assistance system that helps users with text composition across various use cases such as emails, instant messages, and notes. The user can interact with the system through instructions or dictation, and the system generates a well-formatted and coherent document. We describe the system architecture and detail how we address the various challenges while building and deploying such a system at scale. More specifically, our system uses a combination of small, task-specific models as well as pre-trained language models for fast and effective text composition while supporting a variety of input modes for better usability.Comment: Accepted at EMNLP 2023 Industry Trac