Miracle-dz/UniFAR-FTUs huggingface dataset:
uSystolic: Byte-Crawling Unary Systolic Array

General matrix multiply (GEMM) is an important operation in broad applications, especially the thriving deep neural networks. To achieve low power consumption for GEMM, researchers have already leveraged unary computing, which manipulates bitstreams with extremely simple logic. However, existing unary architectures are not well generalizable to varying GEMM configurations in versatile applications and incompatible to the binary computing stack, imposing challenges to execute unary GEMM effortlessly. In this work, we address the problem by architecting a hybrid unary-binary systolic array, uSystolic, to inherit the legacy-binary data scheduling with slow (thus power-efficient) data movement, i.e., data bytes are crawling out from memory to drive uSystolic. uSystolic exhibits tremendous area and power improvements as a joint effect of 1) low-power computing kernel, 2) spatial-temporal bitstream reuse, and 3) on-chip SRAM elimination. For the evaluated edge computing scenario, compared with the binary parallel design, the rated-coded uSystolic reduces the systolic array area and total on-chip area by 59.0% and 91.3%, with the on-chip energy and power efficiency improved by up to 112.2× and 44.8× for AlexNet.
An Homomorphic Logistic Regression Inference Implementation

Abstract Fully Homomorphic Encryption (FHE) makes it possible to perform logical and arithmetic operations on encrypted data that also happens in the underlying plaintext data. For example, let a and b be two numbers, and ε () an encryption function, then: ε ( a ) (cid:13) ε ( b ) = ε ( a + b ), where (cid:13) would be the analogous addition operation for the set of encrypted samples. This property could facilitate data management for cloud service providers while protecting customers’ data against leakage. In this report, we explored the homomorphic encryption using the TFHE scheme [Chillotti et al., 2020] and applied it to the Logistic Regression inference using libraries that already provide a few logical and arithmetic operations, implementing others as needed. We used two sets of data, the ﬁrst a 1994 US census [Kohavi and Becker, 1994] that we employed during the development process and the second a post-surgical breast cancer dataset [Haberman, 1976] for reporting our results. We developed two models, the ciphertext model that worked with encrypted inputs and encrypted weights while the other, the cleartext, worked with cleartext only. This one we employed to ﬁnd the best combination of precision for each ciphertext and the number of bits reserved for fraction so the execution time would be reduced but the inference accuracy preserved. With the ciphertext model, we focused on measuring the execution time. We concluded that the number of features a sample from each dataset needs have a great impact on the overall performance since it sets the number of multiplications required in the inference. Finally, we observed
Natural Algorithms for Optimisation Problems Final Year Project Report

Many computational techniques borrow ideas from nature in one way or another. Neural networks imitate the structure of our human brain, genetic algorithms simulate evolution and swarms of insects inspired algorithms for stochastic combinatorial optimisation. These techniques are characterised by inherent parallelism, adaptivity, positive feedback and some element of randomness. This report details the investigations into certain features of one such technique: the Ant System meta-heuristic proposed by Dorigo. The algorithm is applied to several variations of the well-known Travelling Salesman Problem, including asymmetric and dynamic ones. Furthermore, different approaches to parallelise the algorithm are investigated. Good parameters are needed to instantiate the generic algorithm efficiently and research to find optimal parameter settings has been conducted in the course of this project. An ontology to classify instances of the TSP is introduced and a thorough analysis of the dependency between parameters and classes of problems is presented. During this analysis, optimal parameters have been found for a given problem instance that led to the discovery of a new shortest tour for this instance. A novel algorithm, the Genetically Modified Ant System(GMAS), is then proposed that employs ideas from the field of genetic algorithms to eliminate the need to set parameters for a given problem explicitly. An implementation is described and the new system is evaluated with respect to the standard Ant System and also compared to other more specialised heuristics. The project source code and executables together with all documentation, meeting minutes, outsourcing and final report can be found at: www.doc. ic.ac. uk/∼dg00
Stroke Subtypes, Risk Factors and Treatment Outcomes at A Tertiary Hospital Situated in Rural Southwestern Nigeria: A Five- Year Restrospective Observational Study

Introduction: Despite the high burden of stroke globally, there is an observed paucity of data regarding its subtypes, risk factors and treatment outcomes in rural Southwestern Nigeria. The study ascertained the subtypes, risk factors and treatment outcomes of stroke at the adult Accident and Emergency Department of a tertiary hospital in a rural Southwestern Nigeria. Materials and methods: A retrospective survey using data form and standardized questionnaire was used to review the patients admitted for stroke between January 2015 and December 2019. The data were analyzed using SPSS Version 22.0. The results were presented in descriptive and tabular formats. Results: In this study, 276 stroke patients comprised Ischemic (60.1%) vs Hemorrhagic (39.9%) strokes were studied. The mean age of the patients was 67.3±11.1 years. The majority were males and were older than 65 years. The independent predictors of stroke admissions were Informal education [(AOR = 0.288; 95% CI: (0.120-0.691), p = 0.005)], low income earners [(AOR = 0.452; 95% CI: (0.230-0.888), p = 0.021)], obesity [(AOR = 0.080; 95% CI: (0.019-0.347), p= 0.001)], heart failure [(AOR= 9.152; 95% CI: (2.325-41.266), p < 0.001)], atrial fibrillation [(AOR = 0.136; 95% CI: (0.068-0.891),p = 0.001)], tobacco smoking [(AOR = 0.350; 95% CI: (0.137-0.891), p = 0.028)], and poorly controlled blood pressure [(AOR = 0.107; 95% CI: (0.033-0.348), p <0.001)]. The mortality rate was 10.1%. Conclusion: The results of this study further support the argument on the higher prevalence of stroke admission in rural areas of Southwestern Nigeria. There may be need for public awareness on primary stroke prevention and early identification of the risk factors in order to reduce the prevalence and mortality of stroke in the rural Southwestern Nigeria.
Unmanned Aircraft Platform Based Real-time LiDAR Data Processing Architecture for Real-time Detection Information

LiDAR(Light Detection and Ranging) technology provides realistic 3-dimension image information, and it has been widely utilized in various fields. However, the utilization of this technology in the military domain requires prompt responses to dynamically changing tactical environment and is therefore limited since LiDAR technology requires complex processing in order for extensive amounts of LiDAR data to be utilized. In this paper, we introduce an Unmanned Aircraft Platform Based Real-time LiDAR Data Processing Architecture that can provide real-time detection information by parallel processing and off-loading between the UAV processing and high-performance data processing areas. We also conducted experiments to verify the feasibility of our proposed architecture. Processing with ARM cluster similar to the UAV platform processing area results in similar or better performance when compared to the current method. We determined that our proposed architecture can be utilized in the military domain for tactical and combat purposes such as unmanned monitoring system.
R EVIEW Modeling the speci ﬁ city of protein-DNA interactions

The speci ﬁ city of protein-DNA interactions is most commonly modeled using position weight matrices (PWMs). First introduced in 1982, they have been adapted to many new types of data and many different approaches have been developed to determine the parameters of the PWM. New high-throughput technologies provide a large amount of data rapidly and offer an unprecedented opportunity to determine accurately the speci ﬁ cities of many transcription factors (TFs). But taking full advantage of the new data requires advanced algorithms that take into account the biophysical processes involved in generating the data. The new large datasets can also aid in determining when the PWM model is inadequate and must be extended to provide accurate predictions of binding sites. This article provides a general mathematical description of a PWM and how it is used to score potential binding sites, a brief history of the approaches that have been developed and the types of data that are used with an emphasis on algorithms that we have developed for analyzing high-throughput datasets from several new technologies. It also describes extensions that can be added when the simple PWM model is inadequate and further enhancements that may be necessary. It brie ﬂ y describes some applications of PWMs in the discovery and modeling of in vivo regulatory networks.
Department Informatik

—Writing well-maintainable parallel programs that efﬁciently utilize many processor cores is still a signiﬁcant challenge. Threads are hard to use, and so are event-based schemes. Furthermore, threads are affected by the blocking anomaly, that is, the loss of parallelism when threads execute a blocking system call—often resulting in low core utilization and unnecessarily high response times. This paper introduces pseudo-blocking system calls built upon modern asynchronous queue-based system-call techniques (like Linux’s io_uring ) circumventing the blocking anomaly. They are similar to Go’s programming model, where one develops against a blocking interface to keep the code structure clean. However, instead of using synchronous non-blocking system calls as the underlying technique, our approach internally uses an asynchronous queue-based interface. We further present a novel architecture for concurrency platforms, like Cilk and Go, enabling low latencies and high throughput via pseudo-blocking system calls. Finally, we discuss future OS enhancements that would improve our proposed architecture. We implemented and evaluated a concurrency platform based on the concept of pseudo-blocking system calls. Our platform can outperform state-of-the-art systems like Go by 1 . 17 × in a ﬁle-content search benchmark. It is able to increase the throughput of a echo-server benchmark by 4 % when compared to Go, and by 17 . 8 % when compared to Rust’s Tokio while improving the tail latency.
A Study on the Mental Health Status of Mothers of Young Children in Urban Tamilnadu

Background: Mental health is one of the major public health concerns today. Women, who play multiple active roles in their families experience stress at all levels. This study was conducted to assess the mental health status and its contributory factors in mothers having young children in the urban area of Tamilnadu, India. Methods: A descriptive cross-sectional study was conducted among 200 mothers of young children, regarding their mental health status. All relevant information was collected using a pre-tested, predesigned interview schedule and the parental stress scale. Results: This study has shown that 22% of the mothers were at moderate stress level. Correlation analysis has shown that magnitude of stress is higher in mothers with more number of children and the level of stress is high among mothers having low income for their family. Conclusions: A preventive program including screening of mothers for stress and other psychosocial hazard along with sensitising the need for identifying and seeking help in time will help them to have a better mental health.
The direction of technical change in AI and the trajectory effects of government funding

Government funding of innovation can have a significant impact not only on the rate of technical change, but also on its direction. In this paper, we examine the role that government grants and government departments played in the development of artificial intelligence (AI), an emergent general purpose technology with the potential to revolutionize many aspects of the economy and society. We analyze all AI patents filed at the US Patent and Trademark Office and develop network measures that capture each patent’s influence on all possible sequences of follow-on innovation. By identifying the effect of patents on technological trajectories, we are able to account for the long-term cumulative impact of new knowledge that is not captured by standard patent citation measures. We show that patents funded by government grants, but above all patents filed by federal agencies and state departments, profoundly influenced the development of AI. These long-term effects were especially significant in early phases, and weakened over time as private incentives took over. These results are robust to alternative specifications and controlling for endogeneity.
Performance of PAPR, BER, SER, PER for Multi-User MIMO-OFDM Downlink Scheme and MU Precoding Schemes

The demand for high-quality communication services, anywhere, anytime, is growing rapidly. It is a great challenge for system designers to deal with techniques that improve the provided Quality of Service and reduces the effect of delay spread, Doppler shift. To fulfill this requirement, Orthogonal Frequency Division Multiplexing (OFDM) is an attractive technology, as it deals with the multicarrier modulation. It has several advantages like high data rate transmission with high bandwidth efficiency, exceptional robustness to multi-path fading and low implementation complexity. However, the OFDM system has limitations. The OFDM signal is formed from the linear addition of independently modulated subcarriers. As a result, when the number of subcarriers is large, high amplitude peaks occur which results in high Peak-to-Average Power Ratio (PAPR). Usually, the OFDM signal is passed through a non-linear power amplifier before its transmission over the channel. High PAPR value requires complex high power amplifier (HPA) operating on a very large linear range at the transmitter. Otherwise, the nonlinearity of the HPA leads to in-band distortion, which increases the bit error rate (BER) of the system, and the out-of-band distortion, which introduces high adjacent channel interference. different methods are compared reducing the PAPR, Bit Error, Symbol Error Rate and Packet Error Rate in MIMO-OFDM systems.
A Review of Factors Influencing the Student Motivation for Learning in Virtual Environments

The Coronavirus situation has escorted to the closure of scholastic institutes all around the world. To not interrupt their students’ learning, educational stakeholders had retorted excellently to this challenge by switching to virtual learning and by improving their virtual learning environments (VLEs). Hence, the VLEs have particular characteristics that should be met to accommodate the students’ learning in a trustworthy and successful way. This study aimed to critically review the influential factors of learning in VLEs via a descriptive study. Findings revealed that teacher personality, student autonomy, ICT, and course design are factors related to motivation for learning in a VLE. These findings are considered valuable contributions for educational stakeholders to meet the students’ educational, psychological, social, and technological needs in VLEs which have replaced, in part or whole, the traditional educational systems in most of the educational institutions around the world.
A Secure DNA Cryptosystem based on Steganography and Indexing Cipher

One of the essential challenges nowadays; is how to secure data with the increase of its volume as well as its transmission rate. The most frequent approach used to give a high degree of protection, preserve data from hackers, and accomplish multilayer security is steganography combined with encryption. DNA (Deoxyribonucleic Acid) is considered as a new promising carrier for data security while achieving powerful security and maximum protection. In this paper, a secure DNA cryptosystem model which combines steganography with encryption is introduced and categorized into two layers. The original data are hidden in the first layer into a reference DNA based on the insertion method to obtain a fake DNA sequence. In the second layer, this fake DNA sequence, which is the first layer's output, is encrypted using an indexing cipher to produce an encrypted message in the form of indexes. The proposed model guarantees multilayer security to the secret data with high performance and low-time wasting. It addresses the long-generation key problem of the DNA cryptography. The experimental results assess and validate the theoretical security analysis and model performance.
Producing Health: Measuring Value Added of Nursing Homes

We develop a stylized model that allows us to estimate a value-added measure for nursing homes (“SNFs”) which accounts for patient selection both into and out of a SNF. We use the model, together with detailed data on the physical and mental health of about 6 million Medicare SNF patients between 2011 and 2016, to estimate the value added for about 14,000 distinct SNFs. We document substantial heterogeneity in value added. Nationwide, compared to a 10th percentile SNF, a 90th percentile SNF is able to discharge a patient at the same health level about a week sooner, which is about one third of the median length of stay. Heterogeneity in value added within a market is almost as large as it is nationwide. Our results point to the potential for substantial gains through policies that encourage reallocation of patients to higher-quality SNFs within their market. ∗We thank Alden Cheng, Eric Zwick, and seminar participants at Chicago Booth, Duke/UNC, Tinos IO conference, UBC, UPenn, USC, Rice, and Washington University for comments and suggestions. We are grateful to Sean Gao, Sam Wang, Alicia Weng, Xuyang Xia, Connie Xu, Yuci Zhou, and especially James Okun for superb research assistance, and to the Laura and John Arnold Foundation, and the National Institute on Aging (Finkelstein R01-AG032449) for financial support. †Stanford University and NBER, leinav@stanford.edu ‡MIT and NBER, afink@mit.edu §Stanford University and NBER, nmahoney@stanford.edu. Mahoney is currently at the White House, on leave from Stanford; all his work on this paper was done while he was still at Stanford.
Synthesis, Characterization and Antimicrobial Activities of Schiff Base Complexes of Co (II) and Cu (II) Derived from Salicyldehyde and Diphenylamine

This paper reports antibacterial and antifungal activities of Schiff base and that’s of its metal (II) complexes (Co, Cu) derived from salicyldehyde and diphenylamine. The Schiff base and its metal (II) complexes were characterized using different analytical techniques like FTIR, melting point, solubility, and molar conductance, The Schiff base and its respective metals complexes were colored. The result from IR analysis revealed bands at 1614cm -1 indicating the formation of azomethine (C=N) confirming the formation of Schiff base. The band at 664cm -1 indicate the formation of complex which is assign toV(M-N) supporting coordination of Schiff base to respective metals. The solubility test result showed that both the Schiff base and complexes are soluble in most organic solvent and insoluble in water. Both the schiff base and complexes revealed sharp melting point and decomposition temperature. The molar conductance data of the complexes in Dimethylsulphoxide(DMSO) show low value of 9 and 10 Ohm -1 cm 2 mol -1 ) indicating the complexes are non-electrolytes. The entire compound was tested for their antibacterial and antifungal activities. The results indicated that the growth of the tested organism was inhibited by the compounds. Key word: Schiff Base, Synthesis, Complexes. Copyright © 2022 The Author(s): This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY-NC 4.0) which permits unrestricted use, distribution, and reproduction in any medium for non-commercial use provided the original author and source are credited.
Undersampled Digitally Heterodyned SFGPR with Variable Sampling Frequency

In this paper, an innovative architecture of an udersampled digitally heterodyned stepped frequency GPR is presented. Tipically SFGPR perform a quadrature downconversion in the analog domain to detect targets; the main disadvantages of this approach can be eliminated by performing it in the digital domain. In order to perform such digitally downconversion, the echoes of the step frequencies transmitted are subsampled with a sampling frequency variable on a step by step basis according to rules described hereafter. This approach allows to greatly simplify both the transmitting and receiving chains of the SFGPR by eliminating a frequency conversion stage. The key aspects of architecture presented and its advantages are discussed. It is well known that the capability of electromagnetic waves to propagate beyond the physical dis- continuities of propagation media makes it possible to exploit them to investigate internal features of dielectric bodies. From this property, an endless number of practical applications have been arisen, ranging from medical prospecting to detection of mines, nondestructive testing of industrial items and GPR applications. In this paper, a new architecture of an Undersampled Digitally Heterodyned SFGPR with variable sampling frequency is presented. This design starts by the technical knowledge and on fleld experience achieved during the design of a SFGPR developed in the framework of the ARCHEO project; it was funded by the Italian Ministry of the scientiflc research and industry whose main aim was the development of tools to aid the archeologists in their on fleld researches (1). The key aspects and the advantages of the architecture herein presented are discussed.
Photoluminescence quantum yield of transition metal dichalcogenide

Photoluminescence quantum yield (PLQY) is an important characteristic of luminescent materials. Photoluminescence (PL) is light emitted by a luminescent material after absorbing photons. Quantum yield (QY) is defined as the number of times a specific event occurs per photon absorbed by the system, Transition metal dichalcogenide (TMD) is a kind of material with the type of MX2. TMD is a semiconductor material, but also a two-dimensional material. Single-layer TMD has the properties of large exciton and trion binding energy, which are appropriate in the development of optoelectronics. PLQY is a good method to measure the optoelectronic properties of TMD materials.