bluuebunny/crossref_metadata_2025 huggingface dataset:
Plausible sealing for gradual parametricity
Authors: Labrada Elizabeth , Toro Matías , Tanter Éric , Devriese Dominique
Published: April 2022

Graduality and parametricity have proven to be extremely challenging notions to bring together. Intuitively, enforcing parametricity gradually requires possibly sealing values in order to detect violations of uniform behavior. Toro et al. (2019) argue that the two notions are incompatible in the context of System F, where sealing is transparently driven by potentially imprecise type information, while New et al. (2020) reconcile both properties at the cost of abandoning the syntax of System F and requiring user-provided sealing annotations that are not subject to graduality guarantees. Furthermore, all current proposals rely on a global form of dynamic sealing in order to enforce parametric behavior at runtime, which weakens parametric reasoning and breaks equivalences in the static language. Based on the observation that the tension between graduality and parametricity comes from the early commitment to seal values based on type information, we propose plausible sealing as a new intermediate language mechanism that allows postponing such decisions to runtime. We propose an intermediate language for gradual parametricity, Funky, which supports plausible sealing in a simplified setting where polymorphism is restricted to instantiations with base and variable types. We prove that Funky satisfies both parametricity and graduality, mechanizing key lemmas in Agda. Additionally, we avoid global dynamic sealing and instead propose a novel lexically-scoped form of sealing realized using a representation of evidence inspired by the category of spans. As a consequence, Funky satisfies a standard formulation of parametricity that does not break System F equivalences. In order to show the practicality of plausible sealing, we describe a translation from Funk, a source language without explicit sealing, to Funky, that takes care of inserting plausible sealing forms. We establish graduality of Funk, subject to a restriction on type applications, and explain the source-level parametric reasoning it supports. Finally, we provide an interactive prototype along with illustrative examples both novel and from the literature.
Le temps des cerises: efficient temporal stack safety on capability machines using directed capabilities
Authors: Georges Aïna Linn , Trieu Alix , Birkedal Lars
Published: April 2022

Capability machines are a type of CPUs that support fine-grained privilege separation using
capabilities
, machine words that include forms of authority. Formal models of capability machines and associated calling conventions have so far focused on establishing two forms of stack safety properties, namely local state encapsulation and well-bracketed control flow. We introduce a novel kind of
directed
capabilities and show how to use them to make an earlier suggested calling convention more efficient. In contrast to earlier work on capability machine models we do not only consider integrity properties but also confidentiality properties; we provide a unary logical relation to reason about the former and a binary logical relation to reason about the latter, each expressive enough to reason about temporal stack safety. While the logical relations are useful for reasoning about concrete examples, they do not on their own demonstrate that stack safety holds for a large class of programs. Therefore, we also show full abstraction of a compiler from an overlay semantics that internalizes the calling convention as a single call step and explicitly keeps track of the call stack and frame lifetimes to a base capability machine. All results have been mechanized in Coq.
Effects, capabilities, and boxes: from scope-based reasoning to type-based reasoning and back
Authors: Brachthäuser Jonathan Immanuel , Schuster Philipp , Lee Edward , Boruch-Gruszecki Aleksander
Published: April 2022

Reasoning about the use of external resources is an important aspect of many practical applications. Effect systems enable tracking such information in types, but at the cost of complicating signatures of common functions. Capabilities coupled with escape analysis offer safety and natural signatures, but are often overly coarse grained and restrictive. We present System C, which builds on and generalizes ideas from type-based escape analysis and demonstrates that capabilities and effects can be reconciled harmoniously. By assuming that all functions are second class, we can admit natural signatures for many common programs. By introducing a notion of boxed values, we can lift the restrictions of second-class values at the cost of needing to track degree-of-impurity information in types. The system we present is expressive enough to support effect handlers in full capacity. We practically evaluate System C in an implementation and prove its soundness.
Applying cognitive principles to model-finding output: the positive value of negative information
Authors: Dyer Tristan , Nelson Tim , Fisler Kathi , Krishnamurthi Shriram
Published: April 2022

Model-finders, such as SAT/SMT-solvers and Alloy, are used widely both directly and embedded in domain-specific tools. They support both conventional verification and, unlike other verification tools, property-free exploration. To do this effectively, they must produce output that helps users with these tasks. Unfortunately, the output of model-finders has seen relatively little rigorous human-factors study.

Conventionally, these tools tend to show one satisfying instance at a time. Drawing inspiration from the cognitive science literature, we investigate two aspects of model-finder output: how many instances to show at once, and whether all instances must actually satisfy the input constraints. Using both controlled studies and open-ended talk-alouds, we show that there is benefit to showing negative instances in certain settings; the impact of multiple instances is less clear. Our work is a first step in a theoretically grounded approach to understanding how users engage cognitively with model-finder output, and how those tools might better support users in doing so.
Purity of an ST monad: full abstraction by semantically typed back-translation
Authors: Jacobs Koen , Devriese Dominique , Timany Amin
Published: April 2022

In 1995, Launchbury and Peyton Jones extended Haskell with an ST monad that allows the programmer to use higher-order mutable state. They informally argued that these state computations were safely encapsulated, and as such, that the rich reasoning principles stemming from the
purity
of the language, were not threatened.

In this paper, we give a formal account of the preservation of
purity
after adding an ST monad to a simply-typed call-by-value recursive lambda calculus. We state and prove full abstraction when embedding the pure language into its extension with ST; contextual equivalences from the pure language continue to hold in the presence of ST.

Proving full abstraction of compilers is usually done by emulating or
back-translating
the target features (here: ST computations) into the source language, a well-known challenge in the secure compilation community. We employ a novel proof technique for proving our full abstraction result that allows us to use a semantically (but not syntactically) typed back-translation into an intermediate language. We believe that this technique provides additional insight into our proof and that it is of general interest to researchers studying programming languages and compilers using full abstraction.

The results presented here are fully formalized in the Coq proof assistant using the Iris framework.
Translating canonical SQL to imperative code in Coq
Authors: Benzaken Véronique , Contejean Évelyne , Hachmaoui Mohammed Houssem , Keller Chantal , Mandel Louis , Shinnar Avraham , Siméon Jérôme
Published: April 2022

SQL is by far the most widely used and implemented query language. Yet, on some key features, such as correlated queries and NULL value semantics, many implementations diverge or contain bugs. We leverage recent advances in the formalization of SQL and query compilers to develop DBCert, the first mechanically verified compiler from SQL queries written in a canonical form to imperative code. Building DBCert required several new contributions which are described in this paper. First, we specify and mechanize a complete translation from SQL to the Nested Relational Algebra which can be used for query optimization. Second, we define Imp, a small imperative language sufficient to express SQL and which can target several execution languages including JavaScript. Finally, we develop a mechanized translation from the nested relational algebra to Imp, using the nested relational calculus as an intermediate step.
End-to-end translation validation for the halide language
Authors: Clément Basile , Cohen Albert
Published: April 2022

This paper considers the correctness of domain-specific compilers for tensor programming languages through the study of Halide, a popular representative. It describes a translation validation algorithm for
affine
Halide specifications, independently of the scheduling language. The algorithm relies on “prophetic” annotations added by the compiler to the generated array assignments. The annotations provide a refinement mapping from assignments in the generated code to the tensor definitions from the specification. Our implementation leverages an affine solver and a general SMT solver, and scales to complete Halide benchmarks.
Bugs in Quantum computing platforms: an empirical study
Authors: Paltenghi Matteo , Pradel Michael
Published: April 2022

The interest in quantum computing is growing, and with it, the importance of software platforms to develop quantum programs. Ensuring the correctness of such platforms is important, and it requires a thorough understanding of the bugs they typically suffer from. To address this need, this paper presents the first in-depth study of bugs in quantum computing platforms. We gather and inspect a set of 223 real-world bugs from 18 open-source quantum computing platforms. Our study shows that a significant fraction of these bugs (39.9%) are quantum-specific, calling for dedicated approaches to prevent and find them. The bugs are spread across various components, but quantum-specific bugs occur particularly often in components that represent, compile, and optimize quantum programming abstractions. Many quantum-specific bugs manifest through unexpected outputs, rather than more obvious signs of misbehavior, such as crashes. Finally, we present a hierarchy of recurrent bug patterns, including ten novel, quantum-specific patterns. Our findings not only show the importance and prevalence bugs in quantum computing platforms, but they help developers to avoid common mistakes and tool builders to tackle the challenge of preventing, finding, and fixing these bugs.
Unsupervised Word Segmentation with Bi-directional Neural Language Model
Authors: Wang Lihao , Zheng Xiaoqing
Published: April 2022

We propose an unsupervised word segmentation model, in which for each unlabelled sentence sample, the learning objective is to maximize the generation probability of the sentence given its all possible segmentations. Such a generation probability can be factorized into the likelihood of each possible segment given the context in a recursive way. To capture both the long- and short-term dependencies, we propose to use a bi-directional neural language model to better extract the features of the segment’s context. Two decoding algorithms were also developed to combine the context features from both directions to generate the final segmentation at the inference time, which helps to reconcile word-boundary ambiguities. Experimental results show that our context-sensitive unsupervised segmentation model achieved state-of-the-art at different evaluation settings on various datasets for Chinese, and the comparable result for Thai.
On the Importance of User Backgrounds and Impressions: Lessons Learned from Interactive AI Applications
Authors: Nourani Mahsan , Roy Chiradeep , Block Jeremy E. , Honeycutt Donald R. , Rahman Tahrima , Ragan Eric D. , Gogate Vibhav
Published: April 2022

While EXplainable Artificial Intelligence (XAI) approaches aim to improve human-AI collaborative decision-making by improving model transparency and mental model formations, experiential factors associated with human users can cause challenges in ways system designers do not anticipate. In this article, we first showcase a user study on how anchoring bias can potentially affect mental model formations when users initially interact with an intelligent system and the role of explanations in addressing this bias. Using a video activity recognition tool in cooking domain, we asked participants to verify whether a set of kitchen policies are being followed, with each policy focusing on a weakness or a strength. We controlled the order of the policies and the presence of explanations to test our hypotheses. Our main finding shows that those who observed system strengths early on were more prone to automation bias and made significantly more errors due to positive first impressions of the system, while they built a more accurate mental model of the system competencies. However, those who encountered weaknesses earlier made significantly fewer errors, since they tended to rely more on themselves, while they also underestimated model competencies due to having a more negative first impression of the model. Motivated by these findings and similar existing work, we formalize and present a conceptual model of user’s past experiences that examine the relations between user’s backgrounds, experiences, and human factors in XAI systems based on usage time. Our work presents strong findings and implications, aiming to raise the awareness of AI designers toward biases associated with user impressions and backgrounds.
Modeling Political Activism around Gun Debate via Social Media
Authors: Mejova Yelena , An Jisun , Morales Gianmarco De Francisci , Kwak Haewoon
Published: April 2022

The United States have some of the highest rates of gun violence among developed countries. Yet, there is a disagreement about the extent to which firearms should be regulated. In this study, we employ social media signals to examine the predictors of offline political activism, at both population and individual level. We show that it is possible to classify the stance of users on the gun issue, especially accurately when network information is available. Alongside socioeconomic variables, network information such as the relative size of the two sides of the debate is also predictive of state-level gun policy. On individual level, we build a statistical model using network, content, and psycho-linguistic features that predicts real-life political action, and explore the most predictive linguistic features. Thus, we argue that, alongside demographics and socioeconomic indicators, social media provides useful signals in the holistic modeling of political engagement around the gun debate.
Android Application for an Efficient Method of Tracking and Managing Pharmacies
Authors: Pradhan Rohan , Singh Akarsh KUMAR , Saxena Kshitij , Saxena Rohit
Published: April 2022

This paper focuses on creating an Android application in which the users will be able to search their required medicines, along with the required quantity, and will be able to see all the nearby pharmacies having the required medicines, and then they can easily navigate to the pharmacy, which solves the problem mentioned above. Apart from the customers/users, the pharmacists will also benefit from the app as they can keep a track of all the medicines and medical apparatus in their shop, along with their quantities, and can also update this data regularly on the application. This application is named “PharmaSpotter” as it will help the customers to spot the pharmacies near them quickly.
Studies of Electro-Optic and Thermal Behaviour of Azo Dye Doped Vertically Aligned Liquid Crystal
Authors: Jaggi Chinky , Kumar Pankaj , Malik Praveen
Published: April 2022

The performance of liquid crystal (LC) display devices significantly depends on the usage of an optimized concentration of dopant. Thus, in the present study, vertically aligned liquid crystals (VALCs) display cells were prepared using dispersion of zinc oxide (ZnO) nano particles into host nematic liquid crystal (NLC) without any surface treatment. Further, the sample mixture was doped with fixed concentration of 0.5% of azo dye. Both the sample cells were analyzed and compared for morphological, electro-optical (E-O) and thermal behaviour. Results show the improvement in voltage-transmittance characteristics with lowering of threshold and operating voltage, however the contrast ratio (CR) for dye doped sample cell was found to be degraded. This degradation may be possibly due to much lower transition temperature at this concentration of dye, which further might because of higher OFF state and lesser ON state transmittance due to disturbance in intrinsic LC order. As, the thermal study showed the doping of 0.5% of azo dye reduced the transition temperature to 410 for dye doped VALC from 680 of VALC sample. Hence, these results indicate that a control amount of dichroic dye is a crucial measure for an adequate performance of VALC display.
Factors Influencing Building Maintenance Sourcing Decision in Nigeria Southwest Universities
Authors: Faremi Olajide Julius , Ajayi Oluranti Olupolola , Zakariyyah Ibilola Kudirat , Sotunbo Adegboyega Sunday , John Iniobong Beauty , Kukoyi Patricia Omega
Published: April 2022

Appropriate decision making on either to insource or outsource maintenance services in universities is a strategic task. Such a decision-making process is usually complex and challenging. In the sourcing of maintenance services, different sourcing option suits different maintenance scenarios, hence the need to study the factors influencing decision to insource or outsource maintenance services in universities. Through a cross-sectional survey, data were collected from 112 respondents. The relative influence index and ANOVA test were employed as statistical tools for the descriptive and inferential data analysis respectively. The results show that the development of in-house maintenance staff, technological requirements uncertainty, and the difficulty in getting trustworthy contractors are factors influencing maintenance insourcing, while the need for specialized expertise, strategic alliance with contractors, and the need for specialized management influence maintenance outsourcing. The study concludes that management factors influence insourcing decisions while outsourcing decision are influenced by strategic and technological factors.
Relevance of Psychophysiological and Emotional Features for the Analysis of Human Behavior – A Survey
Authors: Tahseen Saba , Danti Ajit
Published: April 2022

With fresh development in the area of artificial intelligence and machine learning, the analysis of human physiological and psychological behavior has received greater attention around the world. In this paper, we have provided a detailed survey of the approaches used for human behavior detection considering different modalities with physiological behavior, psychological behavior, and emotion detection with the help of sensors EEG, ECG, GSR, and temperature. At long last, it finishes up with the results of this study and represents the thoughts for future exploration in the zone of human behavior understanding. A rundown and comparison among the ongoing investigations is done that uncovers the currently existing issues. In addition, future work has been examined.
Biomechanical Analysis of Multi-Material Hip Implant Assembly
Authors: Joshi Tanuj , Sharma Ravikant , Mittal Vinod Kumar , Gupta Vikas
Published: April 2022

In present work, a 3D multi-material Charnley’s femoral stem with standard geometry model, i.e., 28mm diameter femoral head and 2mm thick liner, has been developed and analyzed for mechanical behavior like stress, strain, and deformation. An axial load of 2.3kN has been used to analyze for twelve multi-material combinations of CoCr and Ti materials for stem, with three femoral head ceramics materials (alumina, zirconia, and ZTA) and UHMWPE for liner. These mechanical parameters are also well validated with published literature and have been evaluated for investigating the functionality and suitability of biomaterials. Changing the femoral head does not make any significant impact on the mechanical parameters. The preliminary simulation result demonstrates that CoCrMo with Zirconia and UHMWPE demonstrates the most minimum deformation and maximum stress generation. However, CoCrMo leads to modulus mismatch due to its very high modulus. So, implant with less deformation and moderate stress, i.e. Ti-6Al-7Nb is preferred over CoCrMo.
A Personalized Supermarket Product Recommendation System Using Augmented Reality
Authors: Deshpande Manasa , B Likhita , Bhat Nayana
Published: April 2022

The online shopping industry has exploded in recent years leading to many benefits. With extensive advertising on social media, electronic platforms bombard people with things to buy, by making suggestions based on the users’ purchases and market trends. Online shopping offers significant advantages, such as the convenience of browsing and ordering from various sites at any given time, but a notable drawback is customers cannot directly see the products while ordering them. While supermarkets allow customers to explore various products before buying them, they are large places and have an extensive product range, which makes it difficult for customers to find desired items and their discounts easily. Product recommendations based on other users’ shopping patterns help users buy items easily and decrease the time taken to look for related items. This feature is currently not available in offline stores. Therefore, a product recommendation system that uses Augmented Reality is proposed. The system also provides in-store navigation using Augmented Reality to help users go to different sections of the supermarket. This system would help customers locate products easily and makes the application more interactive and engaging.
Effect of Nano Reinforcement on Aluminium Metal Matrix Composites: A Review
Authors: Darji Yashesh , Patel Dilip
Published: April 2022

The developing prerequisite for the item having ease alongside amazing quality has encouraged work towards composites of materials lately. Which are having particular stages and qualities just as better than the parent materials. Metal Matrix composites (MMCs) are continually advancing because of inventive and energizing advances and are broadly utilized just as perceived as a possible material for some mechanical applications in different industry. This examination represents applications of aluminum compound primary parts are numerous in vehicles, airplanes, and other military components because of their improved properties and solidarity to weight proportions. New class of AMMC are in consideration wide cluster of utilizations in ventures due to great mechanical attributes, ease, and light weight. Aluminum Metal Matrix composites likewise can be made through an assortment of methods. By various strategy for the manufacture cycle and by adding the diverse support material, distinctive trademark profile got. Objective of this investigation is to study about of creation measure and different components, which are affecting of nano reinforcement on Aluminum Metal Matrix composites.
Video Editing: Technical Vs.Creative Tool
Authors: Chauhan Rajesh Kumar , Kalia Gitanjali , Mishra Ashutosh
Published: April 2022

The audio and video editing software market are expected to increase at a growth rate (CAGR) of 11.24% as per the Technavio report by 2024 [1]. Video editing is the unique aspect of the filmmaking process that involves cutting and assembling segments of shot footage to create a cohesive story. Since its inception, video editing has transformed itself tremendously from a series of transition from kinetograph device (better as 'cutting and sticking ') used in early stage of editing to art of manipulating the viewers emotionally with the Kuleshov effect. Later came Non-linear video editing that could locate a frame within seconds and go back to the edit to change. Through this technical development, filmmakers have always understood video editing as a technical stream rather than the creative. In this research paper, the researcher tries to explore the technicality of video editing skills used in filmmaking since its inception. The paper also explores the extent to which the creative side of the video editing has been studied and understood.
Elliptic Curve Cryptography Applied for (k,n) Threshold Secret Sharing Scheme
Authors: Challarapu Neelima , Chivukula Suneetha
Published: April 2022

Invention of Secret Sharing Scheme by Adi Shamir, along with the prevalent advancements offers strong protection of the secret key in communication network. Shamir’s scheme, which is established using Lagrange Interpolation polynomial. The group manager or dealer of the group splits the secret S to be communicated into n pieces allots all the n pieces to n participants. A subgroup of t or more participants of the group come together to reconstruct the secret key. Later, the cryptanalysis of secret sharing scheme came into picture in the direction of cheater detection whose motivation is to fool the honest participants. The present paper goals to describe a modification to (k,n) threshold secret scheme using elliptic curve cryptography to avoid the dishonest shareholders and faked shares. In this scheme, the group manager or dealer distributes the shares among the participants as affine points on the elliptic curve so that the share modification by the participants or faked shares can be easily detected.
Impact of Lockdown Measures on Air Quality: A Case Study of Jodhpur
Authors: Kumhar Kamlesh , Kumar Ravish , Maheshwari Shobhit
Published: April 2022

Air Quality Index (AQI) technique has been used to analyze and gather database on pollution in the atmosphere. As air pollution is becoming a bigger threat with modernization, various countries are taking different measures to assess the amount of contamination present in the air we breathe. The current research has analyzed the impact of the pandemic on the air quality of Jodhpur and has compared AQI recorded monthly. Changes in the air quality were observed throughout the year 2020. Measurements for four sites in Jodhpur were compared and recorded. To measure the AQI of all the four, “Maximum Operator Function” method, initially tested in IIT Kanpur, was applied. Basni Industrial Area succeeded Shastri Circle and recorded the best air quality. Since both were categorized as industrial areas, it showed that policy measures relating to the industries in the city during past years have helped in improving the air quality.
Microbial Fuel Cells and Genomics: A Review
Authors: Rao Amulya , Rath Abhipsa , Sharma Riya , Meda Ujwal Shreenag
Published: April 2022

With the depletion of fossil fuels, the world is looking towards green energy for electricity production and environmentalists are emphasizing the importance of green energy production. The huge production of biodegradable waste from various sources that are not recycled or treated appropriately is polluting the natural resources. There are many challenges associated with the disposal or reuse of biowastes and in this scenario Microbial Fuel Cells (MFCs) comes into the picture. MFCs generate electricity and hydrogen using wastewater and also bring down the concentration of organic pollutants present in the wastewater thereby purifying it to an extent. Exoelectrogens either present in the wastewater or added externally break down the organic matter into simpler compounds. Distinct parameters that significantly influence the performance of MFC are the microorganisms and to enhance the working, various microorganisms need to be explored and the best ones should be employed. With the help of genomics, we found out the microorganisms that are suitable for enhancing the efficiency of MFC. This was done with the help of certain tools of genomics. MFC and genomics are two varied and diverse topics and in this review paper we try to bridge the gap between them.
The Role of Behavioural Intentions in Implementation of Bitcoin Digital Currency Factors in Terms of Usage and Acceptance in New Zealand: Cyber Security and Social Influence
Authors: Younus Ahmed Muayad , Tarazi Ramzi , Younis Hala , Abumandil Mohanad
Published: April 2022

Bitcoin, Dogecoin, Litecoin, Dash coin, Ripple, and Stellar are just a few of the numerous cryptocurrencies available today. Bitcoin is the most widely used cryptocurrency in various parts of the world. The objective, of this research to ascertain analyses the beneficial effects of social affect and cybersecurity on the use and acceptance of bitcoin.to ascertain and analyses the beneficial influence of examines the behavioural intention as a moderating factor, the relationship between social influence and cyber security and bitcoin use behaviour and acceptance in New Zealand. 497 questionnaires were distributed, and 328 completed questionnaires were returned and analysed, yielding a response rate of 68%. respondents provided their information voluntary a unique link emailed to every one of our samples. the survey. Used hierarchical moderated regression analysis to test the hypotheses (H1, H2, H3, H4). Spss were used to test two sets of linear regression models. the data collection instrument for this study was an online questionnaire. according to the findings, behavioural intention has a significant beneficial effect on social influence and cybersecurity on bitcoin use behaviour and acceptance. additionally, social influence, as well as cybersecurity, have a support positive impact of bitcoin use behaviour and acceptance in New Zealand. the implications for the research on the use of bitcoin are expected to provide education about bitcoin. enhance the security of financial transactions, provide informative pertaining for the regulation that permit use and provide benefits for entice and retain customers in terms bitcoin users. Technological advancements have resulted in a significant
An Empirical Study of Factors Contributing to International Patients Satisfaction with Special Reference to Medical Tourism in India
Authors: Shah Suraj , Vasavada Maurvi , Karim Arzina
Published: April 2022

This work aims at determining the factors contributing to satisfaction of foreign patients after receiving medical treatment in India. For this analysis, convenience sampling is employed under the non-probability sampling methodology. For research purposes, the sample size was taken from 391 individuals. The respondents were those from other countries of the world who wanted to seek medical care in India. The source of the data was primary and secondary both. In this analysis, primary data were gathered using survey process, and patients abroad replied to standardized questionnaires. Data analysis concludes that there is strong significance of choice of destination selection by foreign patients based on quality and cost of treatment, and also one-stop multi medical treatment facility and less waiting time. Hardly few research on medical tourism have been conducted in India. There is a void on this subject in Western India that will bring more expertise and information to the small pool available that will provide new avenues for academia, the business world, and society as a whole.
The Performance Analysis and Security Aspects of Manet
Authors: Singamaneni Kranthi , Alotaibi Abdullah Shawan , K Sri Vijaya , Pandey Purnendu Shekhar
Published: April 2022

Mobile Ad hoc NETwork (MANET) is a type of network that is built by connecting a number of mobile devices together in a temporary manner through impermanent connections. Through broadcasting, the information should be distributed to all nodes in the network. A MANET is a network of self-configurable mobile nodes that are connected wirelessly. The security aspect of MANET is a major challenge, and there is a great deal of research being done in this area. The availability of energy is a critical criterion for a decentralised network. The protocol for AODV and DSR routing, as well as the security of the black hole node, are all investigated in this study. Protocols that are used during the route discovery process are particularly vulnerable to attack by the black hole. The goal of this survey, as a result, is to thoroughly investigate black hole attacks while also evaluating the performance of AODV and DSR during black hole attack scenarios. With Network Simulator 3, the work is completed by simulating both protocols under normal operation as well as under a black hole attack. The work is completed with Network Simulator 3 by simulating both protocols under a black hole attack (NS-3). AODV is more vulnerable to a black hole attack than the DSR, according to the results of simulations, and this vulnerability is greater under normal operating conditions. It has been discovered that MANET attacks are carried out with the assistance of a "black hole," according to simulation results.
A Systemic Review on Human Capital Investment: The Context of Jordan
Authors: Siam Ibrahim , Abumandil Mohanad , Jafri Amira Rafhan , Alshuaibi Mohammad
Published: April 2022

This study investigates the relationship between innovation and human capital investment, and to show how the implementation of these two concepts leads to economic development. After carefully examining the extant literature and by utilizing relevant academic-based research databases, a total of 73 papers published in peer-reviewed journals over the last decade were reviewed and analyzed using well-established systematic literature review methodology. The findings identified four main pillars required to support economic development and achieve a competitive advantage using the country’s human capital: Habitation, Opportunity, Power Distance, and Entrepreneurship (HOPE). The findings also indicated that Jordanian culture is highly germane to all four pillars, which can encourage innovative human capital and ensure economic development. This paper is important to the Jordanian community and the Arab world in general, which lacks awareness of the importance of human capital in socio-economic development. The study helps understand innovation and economic development in the region. This paper explores the relationship between innovation and human capital investment, and shows how this combination will lead to the development of Jordanian culture and the economy.
A System for Monitoring of COVID-19 Patients at Home Based on Internet of Things and Fog Computing
Authors: Mala Deep , Anand Abhineet , Trivedi Naresh Kumar
Published: April 2022

The number of elderly persons, who generally have chronic illnesses and have seen a substantial spread of the novel coronavirus in recent years, has grown in recent years (COVID-19). The majority of older persons suffering from various chronic diseases have died as a result of infection with this virus. Thousands of people have died as a result of this. Coronavirus has also caused several problems in hospitals, and people are not being treated as a result of the large number of patients who require medical care. Medical and paramedic personnel have also been infected, and there is a risk that the virus will spread to the patient and his attendants via medical and paramedical workers. You may avoid this problem by staying at home, where you can monitor your whereabouts and warn in an emergency. The Internet of Things was critical in real-time monitoring of COVID-19-infected patients. Many cloud-based IoT applications are available; nevertheless, high latency, bandwidth, and energy consumption are significant concerns with cloud computing. Fog Computing attempts to address cloud computing issues, such as bandwidth, network latency, and energy consumption. Similarly, one of the primary fog computing applications is data handling generated by healthcare IoT devices. Healthcare IoT devices generate a large amount of data, which must be managed effectively with low latency, no failures, low energy consumption, low cost, and high accuracy.
Ionospheric Model Development for Indian Region: A Survey Paper
Authors: Prajapati Parinda , Patel Nimisha
Published: April 2022

Ionosphere’s role is most important in vigorous satellite communication for the navigation positional correctness purpose. Ionosphere contains diverse layers reliant on its electron density with altitude in the layer. There are various ionospheric models to forecast electron density with temporal resolutions cited by literatures. GPS data is frequently used by these models. So, the necessity is a prerequisite of evolving ionospheric models with different time duration for low latitudes of India. Also, an ionosphere tomography is considered as an ill-posed problem. Ionospheric TEC found simultaneously at numerous locations can be preserved with several algorithms to conquer electron density. This research is proposed for evolving a model to forecast 3D tomography of total electron density for the whole Indian region. Mainly used satellite data can be collected by various means. The management of vast statistics are planned by using data mining techniques and artificial neural network techniques for estimation. This paper is an outcome of detailed research on ionospheric model development.
Assessment of Fracture Resistance of Cranberry and Grape Seed Extract Intracanal Medicament
Authors: Shakir Arshiya , Pushpalatha C , Cherian Larissa
Published: April 2022

Plant extracts, specifically cranberry and grape seed extract, have recently been shown to have remineralizing potential for enamel and dentine. Hence, the aim of the study is to assess the effect of a newly formulated intracanal medicament using cranberry and grape seed extract on the fracture resistance of root dentine compared to chlorhexidine and saline. The root canals of orthodontically extracted premolars (n = 16) were instrumented and randomly divided into four groups: the cranberry seed extract group, the grape seed extract group, the chlorhexidine (CHX) group, and lastly, the saline group was used as control. Results showed that the chlorhexidine group had slightly less fracture resistance of the root in comparison to the cranberry ICM and grape seed ICM groups. Hence, the study concluded that the addition of cranberry and grape seed extract into the intracanal medicaments improves the fracture resistance property.
Inverse Laplace Transform of the Incomplete H-Function
Authors: Ghiya Neeti , Sridevi K , Manjula S
Published: April 2022

Special functions have enormous applications in theoretical and applied mathematics. This field is constantly expanding and addressing new problems in engineering applications and applied sciences. H-function one and more variables have been applied in large range of areas, such as electronics and communication, astrophysics, fractional differential equations, super statistics, diffusion, reaction–diffusion, and other fields like probability theory, biology, and theoretical physics. Some situations of heat conduction and astrophysics problems are not adequately addressed by basic category of special functions. To address such problems, incomplete special functions found the way in the literature. Incomplete H-functions are attracting researchers working on heat conduction and astrophysics problems. The paper aims to transform the products of algebraic powers and incomplete H-function in another domain using inverse laplace transform. Results are obtained in terms of the incomplete H-function as compact form. Further, some particular cases are mentioned by giving special values to the incomplete H-function’s parameters.
Positive Psychology Goes to School: Conceptualizing Students’ Happiness in 21st Century Schools While ‘Minding the Mind!’ Are We There Yet? Evidence-Backed, School-Based Positive Psychology Interventions
Authors: Alam Ashraf
Published: April 2022

The purpose of this article is to examine school-based interventions that have been designed and developed to promote students’ happiness, well-being, and academic achievement using a positive psychology approach that focuses on cultivating positive emotions, resilience, and positive character strengths. The current paper outlines the positive psychology movement and reviews evidence from 12 school-based positive psychology interventions that have been systematically evaluated, in response to calls from the 21st century education movement for schools to incorporate students’ happiness and well-being as a focus of learning. The findings of this research shows that positive psychology programs are linked to students’ health, relationships, happiness, and academic success. The article offers recommendations for additional development of positive psychology interventions in schools, and explores those factors and variables that may influence positive psychology interventions to be extended and more systematically integrated into schools for happiness and well-being of students.
MEMS Technology for Early Stage Diesis Detection Using Micro-Cantilever Structure in Support of Biomedical Applications
Authors: Shukla Kaustubh Kumar , Muthumanickam T.
Published: April 2022

This research work is addressing the goal of achieving good health and well-being of human being by attempting the detection of a target analyte (HIV or other bimolecular analyte) using microcantilever. It is helpful to detect the bio-analytes because of its high sensitivity, selectivity, and structural simplicity. Depending on deflection of microcantilever by achieving maximum displacement, the device can be made extremely sensitive. The reason of making the device more sensitive is to detect even a single molecule also. Design has been done in three different stages. In the first stage it was estimated of the more suitable and sensitive sensing material. A second stage investigation has been done for the suitable construction of different shapes by introducing different holes in structure. At third stage research has been done about the multilayer to make the device more sensitive. Finally, concentration is to produce a high sensitive structure to detect the analyte quickly.
Mathematical Modeling of Transient Water Interactions Between a Sloping Aquifer and an Adjusting Stream
Authors: Saxena Shikha , Bansal Rajeev Kumar , Singh Basant Kumar
Published: April 2022

Due to the constantly changing hydrological conditions of the surrounding water reservoirs, estimating water table changes in response to stream-stage variations and downward recharge is an emerging area in hydrology. Mathematical modeling is the emerging tool for predicting water table behavior in many complex geological situations. In this paper, a stream-aquifer model is considered and variations in the water table height have been calculated. At one end, the aquifer is in contact with a constant water level, and at the other end, the water level is rising exponentially from an adjoining stream. An analytical equation is solved by the Laplace Transform method for estimation of water table fluctuations in response to combined effects of bed slope and non-uniform recharge and seepage.
Role of Functional Groups in ILs Decorated Au (111) Surface for CO2 Capture and Activation: A First Principle Approach
Authors: Kamalakannan Shanmugasundaram , Maiyelvaganan K. Rudharachari , Prakash Muthuramalingam
Published: April 2022

A heterogeneous catalytic environment plays a major role to decide the catalytic activation and conversion of the CO2 molecule at the interface. For this, we have chosen functionalized 1-ethyl-3-methylimidazolium cation (i.e. [EMIm-Z]+[X]-, where Z = NH2 and CF3) with two different anions (i.e. [X]- = [DCA]- and [SCN]-). Our results reveal that the electron donating groups at the interface can effectively activates and converts CO2 to radical anion. But the electron-withdrawing (i.e. –CF3) substituent lowers the binding strength of CO2. Besides, the adsorption and activation mechanism of CO2 at the interface is directly influenced by the involvement of the -NH2 functional groups in the ([EMIm]+) cation. It is identified that the different types of intermolecular interactions between the CO2 and interface. Such as (i) O=C=O····H(-NH2), (ii) O=C=O····H (-CH3)), (iii) O=C=O····F(-CF3). Our work provides a clear picture about the role of the functional group at the interfacial medium for activation of CO2.
Machine Learning Techniques in Business Forecasting: A Performance Evaluation
Authors: Sajja Guna Sekhar , Pallathadka Harikumar , Phasinam Khongdet , Arcinas Myla M.
Published: April 2022

Business forecasting is the act of looking at how businesses have done in the past in order to use that information to predict how businesses will do in the future so that business strategies can be made to reach goals. Recent computer and technological changes have made it easier for businesses to collect and store data that can be used to make business decisions. If you want to make better decisions and plan better for your business, you use business forecasting to help you do that. It allows people to figure out important parameters and variables that can be controlled in advance so that management-oriented results can be achieved in the future. In simple terms, business forecasting is the act of predicting or projecting future trends based on company data. Forecasting is becoming more important in today's business world because companies are trying to make their customers happier while also cutting down on the costs of making and selling things and things. When a man runs a business, he has to try to figure out what will happen in the future, and his success or failure is very much dependent on how well he can predict the future. Forecasting tries to cut down on the uncertainty that managers have had to deal with when it comes to things like cost, profit, sales, production, and pricing. This article talks about how machine learning can be used to predict business outcomes.
A Hybrid Algorithm for Face Recognition System Based Smart Attendance System
Authors: A Sathya , L Priya , S Dhanalakshmi
Published: April 2022

Face recognition aims to detect, track, identify, or verify person from video or images using recognition system. Its application varies from security, authentication, social media, and so on. With the advancement of technologies, still it impedes in accuracy. The challenges involved in face recognition are variations in facial expression involve diverging light, facial changes interfered with facial hair, pose, and so on. This research work presents a new hybrid approach, which improves the accuracy in identification of a person. The accuracy of the proposed work clearly depicts that it can be best suited in real time environments for tracking persons. It can be used for applications like authentication, security, and so on. The proposed work is validated by tracking the student presence. It captures the image of the student and detect the face by pre-processing, extracting the features and recognizing the person. For recognition it uses Local Binary Pattern Histogram (LBPH) algorithm and Haar Cascade classifier. LBP Algorithm uses Histogram, which improves the accuracy of the face recognition. It is integrated with Haar classifier, which uses machine learning algorithm. Adaboost Learning algorithm, which selects small features from large set, which improves the efficiency of recognition.