Miracle-dz/UniFAR-FTUs huggingface dataset:
Smart Monitoring at the Surface of a Compact Blockchain Privacy Defence

As surveillance video tracking (VSS) is being more and more deployed, more and more people are struggling with concerns related to breaches of data protection. While monitoring for crime dissuasion is favourable for the majority of the population, citizens do not embrace intrusive private life oversight. However, there is currently no easy-to-use and secure video monitoring system privacy preservation solution. This difficult topic has been shed light on the new progress of blockchain (BC) technology besides their Internet of Things (IoT) implementations. In this article we suggest a Blockchain based Lightweight Confidentiality Framework for edge cameras surveillance. It helps the VSS to monitor the discretion of individuals caught in the videos without violating them. The Lib-Pri system converts the used VSS into a system, which acts as a amalgamated blockchain system that controls integrity, handles bubbly keys, shares functions and endorses video entry. The policy implementation of data protection controls on the edge of computers is done without intervening with the network for real-time video analytics.
RETRACTED: Security Protection of Information Utilizing Halfway Speculation

Securing privacy in information-digging (data mining) has become indispensable for buying and selling labelled statistics in statistical evaluation, validation, and guide. In such cases, records are either released in published form for re(use) through others for research functions. Here, privacy takes an extensive role to secure the records from ever-escalating net phishing and different probable attackers. Significant upgrades for strong privateness upkeep and protection have emerged as mandatory. In this paper, we endorse the approach of partial speculation. This technique is essential to mask the information in this sort of manner that different facts mining strategies can be without difficulty applied to it. On the alternative hand, it makes the information okay-nameless for this reason, information cannot be re-identified at the same time as records remain almost useful. In partial speculation, simplest identifiers that are vital are speculated first. If this step, safeguards the records from external information linkage, then the technique no longer speculates besides, preventing extra speculation than important with minimal facts loss.
An Efficient Framework of Human Voice Verification for Robotic Applications

Waves are considered to be used to decode the speech signal more efficiently. This study is an accessible and robust approach for obtaining voice recognition features. Here, we suggested a new text-related method for the identification of human voices (TDHVR) system, which utilizes the discrete wavelet transform (DWT) for low level feature extraction, Relative Spectral Algorithm (RSA) for denoising the voice signal and finally Additive Prognostication (AP) for estimating the formants. First, the proposed methods are used for voice signals, and then we construct a vector train function that includes the derived low level function and estimated formant parameters. The same technique is then applied for calculating speech signals and constructing a test feature vector. The Euclidean distance between the vectors will now be used to balance all vectors in order to distinguish the voice and voice. The simulated human voice would equal the educated person’s speech if the difference between two vectors is almost null. Computation results were compared with the LPC Scheme and revealed, that by using fifty preconfigured six voice signals, verification trials were carried out, and a best accuracy of approximately 90 percent was reached, the suggested methodology surpassed the current methodology.
Effect of sustainable materials on embodied energy, carbon footprint and cost for a proposed conventional apartment

The construction industry accounts for an incredible 36% of worldwide energy usage, and 40% of CO2 emissions. Therefore, it is required to reduce the impact of construction on the environment. In this study, a few green materials have been selected along with few green techniques and are applied to the apartment and a comparison is provided. An ongoing project consisting of 18 typical floors and basement is selected for the study. Estimation of quantities are done according to the drawings and major materials such as blocks, internal paints, flooring and concrete are replaced with proposed sustainable materials. Embodied energy and carbon footprint analysis is performed for the building components such as blocks, tiles, paints, concrete and plastering. Alternate materials like compressed stabilized earth blocks, clay plaster, wallpaper, terrazzo tiles and blended cement concrete are chosen as replacements for the conventional materials. A comparison is provided with conventional materials with respect to the chosen sustainable materials. The results show 73% reduction in embodied energy and 52% reduction in carbon footprint of the structure. Also, reduction in cost by 30%. Hence, reducing the impact on the environment and making the structure sustainable.
Some new applications of β-Laplace integral transform

The β-Laplace integral transform(β-LIT) has been introduced recently by Gaur et. al. which is a generalization of Laplace transform. This new β-LIT shows some special properties over Laplace integral transform. In the current paper, we investigate the applicability of the β-LIT technique to solve partial differential equation such as initial value problem of first order and second order PDE, wave equation, Diffusion equation, Potential and current equation, Heat conduction equation, Axisymmetric Heat conduction equation, Inhomogeneous partial differential equation, inhomogeneous wave equation, Stroke and Rayleigh problem in fluid dynamics and illustrate by some examples.
Blockchain Confidence Protection and Cloud Chain Management Support

Verification and completeness are main challenges for today’s ever more diverse supply chains. Even with the ability to counter blockchain technologies by offering a trail of manipulation-resistant audit It does not address the confidence issue associated with the source chain activities also information related to a produce life cycle Information itself. Reputation mechanisms are a promising solution for this faith problem. Yet existing structures of credibility are Not ideal for supply chain applications based on blockchain as centred on restricted findings, lack of granularity and their overhead was not discussed and automation. We recommend the system as a three-layer faith in this job. Management platform is using a blockchain consortium tracking relationships between actors in the supply chain and Assign trust and prestige dynamically dependent on these interactions. Its novelty is based on a Model for credibility assessing product quality and the trust of individuals based on many observations funding for credibility qualities in supply chain incidents separating the member in the supply chain from the goods, enables brand credibility to be reserved for smart contracts for straightforward use by the same participant, Effective, secure, and automatic credibility scoring measurement, and the latency and throughput minimum overhead as compared to a straightforward supply chain model based on blockchain.
Study of the Usability Testing of E-Commerce Applications

Usability Testing determines the friendliness of the application to meet customers’ requirements. It must be adopted in the early stage of SDLC (Software Development Life Cycle) to avoid issues in a later stage. Today, E-commerce has revolutionized the mode of shopping, and thus, we need to focus on ways to improve the usability of e-commerce applications. We opted for survey questionnaires as our research methodology, along with testing websites using online tools based on the four parameters Connectivity, Readability, Accessibility, and Functional Performance. In the survey, the four most popular e-commerce applications were Amazon, Flipkart, Bigbasket, and Paytm. Out of which, Amazon was the most used e-commerce application by the consumers. Although, testing tools are depicted that applications need to improve in certain areas. From the analysis, we concluded that consumers are aware of the upcoming Jio-Mart, which can give tough competition to existing companies. Thus, all the existing e-commerce companies need to improve their web and mobile applications to retain their customer base.
Development of customized support for the prevention of Pressure Ulcer (PU) using multi-materials printing

Pressure Ulcers (PU) seems to be one of the most challenging healthcare problems around the world. It may result in significant morbidity, mortality and is associated with high cost in terms of treatment and care. PU is considered to be the third most expensive disorder after cancer and cardiovascular diseases. Though, modern medical science has launched a variety of treatment methods, prevention is the best way to overcome. As it could be seen from the current market design, most of the products provide a cushioning effect to the end user, but this lacks in product customization. Further, these products are not custom made to meet the end user needs and these products are expensive to be used. Understanding the above intricacies, the current research is focused entirely to be different from the existing product design, working, manufacturing methods and materials for the development of a product to redistribute the pressure for the reduction of PU. The projected design purely depends only on mechanical materials and mechanical behaviors. In this work, the number of phases of design was carried out through Solid Works software. The deformation and stress analysis was carried for all the design phases for obtaining the better design. Finally, the prototype is developed through Additive Manufacturing (AM) technology with the multi-material combination. The final prototype was evaluated experimentally using emed® sensing platform for the flexibility and pressure distribution also compared with the existing cushions.
Blockchain Infrastructure with Fragments Dependent Security Deposit Solution

Blockchain is considered a shared ledger technology to be a viable alternative for heavily focused control process applications. However, most of the current blockchain networks are used for the proof of work called the Hash-Puzzle-Solving Consensus Protocol. The competition to solve the puzzle leads to high latency, leading directly to a lengthy cycle of transaction processing. One solution to this problem is the establishment of a shards blockchain network. In this article, we concentrate on the blockchain network and follow a consensus protocol on security deposits to explore the issue of how to reconcile the economic reward and incentive. The knowledge asymmetric dilemma between beacon and users is also posed by the intrinsic features of the blockchain, i.e. transparency and decentralization. The philosophy of the contract is used to describe the dilemma. The optimum incentives for the various types of validators as well as the required deposits will also be obtained. The flexible deposits may provide ample economic stimulus for participants relative to fixed deposits without sacrificing the safety incentives. Moreover, the results of simulation suggest that the contract theory strategy will optimize the effectiveness of the beacon chain and fulfil the participants’ reward compatibility and individual rationality.
Comprehensive Analysis of Machine Learning Algorithms Used in Robo-Advisory Services

Adoption of Robo advisory is rapidly increasing among retail investors. Approximately 10% of all assets under management will be managed by them by 2025. Researchers continuously work on finding machine learning and deep learning algorithms which will accurately predict the stock price movement with less error. Various Robo advisor platform providers are working on different approaches like NLP (Natural language algorithm) based sentiment analysis, hybrid time series algorithms to limit human bias, which existed in the current financial advisory services. This research compared the performance of various forecasting algorithms, which can be used in the Robo advisory framework. RMSE (Root mean square value) value is taken into consideration in this research to compare the performance of algorithms as it is a good and simple loss function. It has been observed that newer algorithms like those proposed by Facebook are able to predict stock prices pretty well, but ARIMA outperformed all the algorithms which are considered in this research.
Towards Development of Performance Metrics for Benchmarking SLAM Algorithms

The true autonomy of mobile robots cannot be achieved without Simultaneous Localization and Mapping (SLAM). With this capability, mobile robot could concurrently build a map of the environment and locate itself with respect to the map. Although there are several variants of SLAM algorithms contributed by researchers so far, only a very few works were aimed at comparing their performances with appropriate metrics and providing detailed directions and insights to the user on selection criteria and indicative use cases. In this work, we presented a comparative study of three popular SLAM algorithms and provide some significant quantitative performance measures of the same by using our novel | R | and | S | performance metrics as well as conventional metrics. The comparative study was carried out in ROS (Robot Operating System) using Turtlebot3 robot model on three SLAM packages viz G-mapping, Karto SLAM, and Frontier Exploration SLAM. Furthermore, the results show that the proposed metrics are very efficient and compact in comparing and quantifying the performance of SLAM algorithms.
Analysis of substrate materials for millimeter wave antenna applications

A compact and novel multi band series fed array antenna is simulated and analyzed for antenna applications in millimeter-wave frequency ranges. The single element antenna performance is investigated for different flexible substrate materials like Rogers Ultralam, Arlon Diclad 880, Neltec NY9220, Taconic TLY, Polyethylene and Polystyrene in initial stages. The proposed series fed array antenna operates (S11<-10dB) in 14.7-20.8GHz, 23.125. 8GHz, 28.5-34.8GHz and 39.3-44.8GHz frequency bands. The designed antenna exhibits negative group delay characteristics from 18.2-19.9GHz, 29.9-33.3GHz, 39.4-42GHz and 42.6-43.6GHz. It achieved a peak gain of 13.9dB at 42.5GHz and radiation efficiency of 97.5% at 33GHz. Results obtained are in fine conformity and therefore, proposed antenna is preferable for mmwave applications.
Design of IoT based Platform Development for Smart Home Appliances Control

The advent of industrial automation has brought about a substantial change in the human lifestyle and the way human interaction with machines. One of the major technological interventions in day-to-day life is the role of automation, which has uplifted the living standards in developed countries and fostered humans’ dependency for accomplishing recurring tasks. The latest and most adopted technology for remotely monitoring and controlling any machine or device is the Internet of Things-which has become one of the industry standards for automation. Multiple edge computation capable embedded devices and machines are connected to the internet as independent nodes, which can be monitored and controlled remotely with the use of IoT. Adapting this cutting-edge technology for household appliances to monitor and control them is often seen nowadays. This is fast and reliable but arrives with its own snags such as availability of internet at place where user and also the device/appliance is located, use of single control strategy which hampers and restricts the user always to carry the remote or to stay in the vicinity of the device to be controlled in case of wifi or Bluetooth controlled automation. The proposed research focuses on the adoption of multiple strategies to control each device/appliance to empower the end-user without being restricted to depend on a single strategy remote controlling system. The core part of the proposed research revolves around the Message Queuing Telemetry Transport (MQTT) protocol but can be activated with multiple routes such as touch-based sensing panels, cellphone-based controlling, web-enabled controlling or even gesture-based controlling of the appliances resulting in an ameliorative user experience and interactions with machines.
Performance analysis of Cooperative underlay CRN in NOMA aided Energy harvesting for multiple secondary users

This paper proposes a relaying scheme in an underlay cognitive radio network(CRN), where a source node desires to transmit the information simultaneously to more than two desired destinations. The power required for the relay operation is based on applying energy harvesting from the base station (BS). The proposed paper also includes Non-orthogonal multiple access (NOMA) with fixed power allocation to the different users to perform the decoding process irrespective of the channel condition. We have proposed a mathematical expression for the analysis of outage probability for the different users. In this respect, the linear model is discussed for perfect successive interference cancellation (SIC) at the receiver. Using the fixed power allocation process, we have simulated different output parameters such as Bit Error Rate (BER), NOMA capability, and the outage probability.
Design of Digital Clock Manager Using Tunable BFD–True Random Number Generator

By demanding authentication exercises for example communications, electronic cash frameworks, plate encryption, the cryptographic frameworks have become a core aspect in our daily lives. Random numbers are an significant factor in strengthening and anchoring the protection of e-mail messages used in multiple encryption applications, including key ages, encryption, convention coverage, web wagering. Random flight numbers for basic mystery keys are basic to the protection of criphotographical calculations. In a variety of cryptographic systems, actual random number generators (TRNGs), The part has been incorporated, including PIN / secret word age, validation agreements, key age, random cushions and age of nunce. The circuit uses an undetermined random mechanism as a fundamental source, largely as electric commotion. Programmable field door arrays (FPGAs) are the optimal stage for the success of equipment that offers substantial safety conditions. The TRNG suggested is subject to the Xilinx-FPGA Bit Recurrence Recognition Guideline.
RF Based Lo-Ra Transceiver Patient Health Detection System

In the last century, remote treatment surveillance grew rapidly, along with the increasing number of internet users with things (IoT). Health management, especially because early disease diagnosis can minimize distress and treatment costs, is very important for prevention. The diagnosis and timely care of multiple conditions will dramatically boost patient treatment alternatives: Wireless Clinical Management and Monitoring Device for Patients. Wireless health surveillance system or patient surveillance system requires remotely tracking the critical patients through computers, which transmit patient data wirelessly to distant locations. Health networks based on IoT seek to increase the quality of healthcare services via data collection and analysis in real-time. Nonetheless, conventional IoT systems have several drawbacks. In areas with a weak or unreliable Internet, for example, they cannot operate effectively. Low power large area network (LPWAN) technologies such as long-range network components like LoRa are a viable solution for showing the issue of Internet services. In diagnostic techniques and therapies, monitoring system plays an essential part.
CNN and Computational Configuration Mathematical Chromosomal Defect Analysis in Medical Images

Chromosomal defect analysis plays an important role in current medical care and diagnosis as one of the principal methods in cytogenetics via the processing of a medical picture. There are two main elements of human karyotype analysis: first, chromosomes are separated by digital images of the chromosome metaphase under the microscope. Chromatids are then closely analyzed, compared, organized and categorized. The segmentation and classification operation is tedious, where conventional geometric or mathematical approaches have only limited impact due to low precision, according to this technique. In most cases however, the workflow is still highly supervised and errors are still required by humans. This paper provides an optimised workflow to isolate and automatically identify chromosomes by a combination of many CNN and mathematical optimizations called mCNN GO. Mask R-CNN is investigated to separate the chromosome from chromosome metaphase images and train mCNN GO to identify the sub-images. We apply a new functional approach to synthesize images on the labelled data in order to enhance the efficiency of the segmentation network. Moreover, to ensure accuracy of the results, we create computational algorithms to straighten the genomes before registration. Experimental findings indicate that our methods for automated karyotype analysis are greatly superior to state-of-the-art.
Charging Dynamics and Optimization of Nanoporous Supercapacitors

An improved mean-field model used earlier (J. Phys.: Condens. Matter2011, 23, 022201) to explain the anomalous increase of capacitance in nanoporous supercapacitors is extended to the study of charging dynamics. We find that charging of initially empty (i.e., ionic liquid-phobic) pores proceeds in a front-like way, while charging of filled (i.e., ionophilic) pores is diffusive; in both cases, however, the accumulated charge grows as a square root of time. We also discuss two-step complementary optimization of porous electrodes for supercapacitors. In a first step, the optimal pore width is chosen to maximize the stored energy density; in a second step, the optimal pore depth/length (that is, electrode’s thickness) is chosen to satisfy the requirement on charging times. In addition, the use of “nanoporous channels” in a “multilayered” configuration is suggested to decrease the volume and to increase the capacitance, stored energy, and power density of a supercapacitor.
Transparency and Best Practices are Essential for ESG Investing

Many investors have shifted their asset allocations to account for Environmental, Social, and Governance (ESG) issues. While we welcome this shift from an ethical perspective, the financial and non-financial benefits of ESG investing as well as best practices for portfolio construction are subjects of heated debate. We look at aspects of the debate through a series of practical examples. First, we illustrate the trade-off between risk control and unwanted exposures in energy and “vice” stock exclusions, which have exhibited inconsistent performance at a ten-year horizon. Next, we show how recent underperformance of a gender lens portfolio has been confounded by technology stocks. Finally, we explore how ESG score disparities lead to important differences in portfolios constructed with these scores. In aggregate, our examples point to the inherent complexity of ESG investing, which will benefit from better data, transparency, customization, and an acknowledgement that doing good does not necessarily lead to doing well. An important theme throughout this paper is that everything should be made as simple as possible, but no simpler. ∗Consortium for Data Analytics in Risk, University of California, Berkeley and One Concern, email: jeffrey.r. bohn@gmail.com. †Consortium for Data Analytics in Risk and Department of Economics, University of California, Berkeley, and Aperio Group (now at BlackRock), email: lrg@berkeley.edu. ‡Aperio Group (now at BlackRock), email: Simge.Ulucam@blackrock.com. §We are grateful to Lloyd Han, Mark Bateman, the participants of the Journal of Investment Management Spring 2021 conference and the June 2021 AperioX seminar.