Objective: The present study investigated anti-arthritic potential of mandelic acid (2-hydroxy -2-phenyl -acetic acid) using in-vitro and in-vivo techniques and found the oral acute, sub-acute and sub-chronic toxicity in rats. \nMethod: The in-vitro tests comprised of protein denaturation (bovine serum albumin and egg albumin) and Human Red Blood cell (HRBC) membrane stabilization assays at 50-6400 µg/ML, for in-vivo testing formaldehyde-induced arthritic rats were treated with at 40, 80 and 160 mg/kg mandelic acid (MA). In acute toxicity, single oral dose 2000mg/kg of MA with 48h interval was given to each rat, while in sub-acute toxicity studies rats were treated with 200,400 and 800mg/kg of MA for the period of 14 days. However in sub-chronic toxicity study rats were administered with 40, 80 and 160mg/kg of MA for period of 28 days by following OECD guidelines 407 with minor modifications. \nResults: Mandelic acid inhibited the protein denaturation and stabilized the membrane of HRBC in a concentration dependent manner. Likewise, mandelic acid exhibited dose dependent reduction in paw volume of arthritic rats induced by formaldehyde with highest effect at 160mg/kg dose. For acute and sub-acute treatment MA did not show any sign of toxicity and mortality in each rat for the period of 14 days and LD50 might be greater than 2000mg/kg. In addition histopathological assessment of heart, liver and kidney presented slight increased interstitial spaces in the kidney, disorganization of glomerulus, dilated sinusoids at highest dose 800mg/kg, such abnormalities were not observed in sub-chronic therapy. \nConclusion: Hence, these results conclude that mandelic acid has the potential to treat rheumatoid arthritis with observed no significant signs of toxicity and should be tested further to determine anti-arthritic mechanism of drug action at cellular level.

Internet of things (IoT’s) is one of the most emerging technologies nowadays. It has started to participate in almost every aspect of our social life, ranging from financial transactions to the healthcare system, communication to national security, battlefield to smart homes, and so on. However, the wide deployment of IoT’s suffers certain issues as well, such as interoperability, compatibility, heterogeneity. Among the others, security and energy efficiency are the most prominent challenges. The limited energy and computing resources (e.g. processing power, storage) of IoT’s put hindrances on information sharing across edge or IoT network. Indeed, unintentional or malicious interference with IoT’s data may lead to severe consequences. In this study, we exploit the potential benefits of a blockchain system and integrate it with software-defined networking SDN while mitigating energy and security challenges. More specifically, we proposed a new routing protocol with the cluster structure for IoT networks using blockchain-based architecture for SDN controller. The proposed architecture obviates Proof-of-Work (PoW) with private and public blockchains for Peer-to-Peer P2P communication between SDN controllers and IoT devices. In addition to this, distributed trust-based authentication mechanism makes blockchain even more adoptive for IoT devices with limited resources. The experimental results show that the cluster structure base routing protocol outperforms the state-of-the-art AODV, DSDV, SMSN, EESCFD, and AOMD, in terms of energy consumption, network throughput, and packet latency.

In the present paper a mathematical model of a smart cantilever beam with embedded shear sensors and actuators is developed. The smart cantilever beam model is developed using a piezoelectric sandwich beam element, which includes sensor and actuator embedded on discrete locations and a regular sandwiched beam element, which includes foam at the core. A FE model of a piezoelectric sandwich beam is developed using laminate beam theory in MATLAB®. Each layer behaves as a Timoshenko beam and the cross – section of the beam remains plane and rotates about the neutral axis of the beam, but it does not remain normal to the deformed longitudinal axis. Keeping the sensor and actuator location fixed in a SISO system, state space models of the smart cantilever beam is obtained. The proper selection of control technique is very important in order to obtain the better control. In the article POF controller and FOS feedback controller are designed to control the first three modes of vibration of the smart cantilever beam and their performances are compared on the basis of open loop response, closed loop responses with signal conditioning device and with controller gain, control signal amplitude are investigated. It is found that FOS controller provides better control than the POF controllers.

This study analyzes forestry governance by assessing the local and central government\'s forest\nland-use activities. Collaborative management is often cited for developing a plan for\nsustainable management of forest land use. However, the empirical approach of collective\nleadership is still lacking. First, this research investigates to which factors of collaborative\nmanagement practices respond the forest land use? The local and central government manages\nforest land use and affects deforestation and forest fires. Understanding their roles is essential\nto managing networks for forest management activities. The 2010-18 fires affected agricultural\nland, plantation, forest, and swamp peatland clearing for oil palm and timber plantations\nappears to be the main source of smoke-haze and pointed as the primary driver of land clearing\nmotives in Riau Province, Indonesia. We used Nvivo-12 as the coding tool of each interview\nresult; an observation was coded for discussion and the distilled findings from the analysis.\nThis data was then transferred to the Gephi to allow networking analysis. The network has been\ncombined with Gephi, NVivo can be used to explore forest land-use activities by combining\nnetwork analysis to assess the pattern of collaboration.

The purpose of study was to synthesize bergapten-loaded nanostructured lipid carriers (NLCs) to characterize and develop a HPLC method. The bergapten-loaded NCLs were characterized for particle size (PS), poly dispensability index (PDI) and zeta potential (ZP). The morphology of NLCs was observed by scanning electron microscopy (SEM). The drug encapsulation and loading efficiency were evaluated. Moreover, a HPLC method was developed and validated in terms of accuracy, precision, specificity, linearity, limit of detection, limit of quantitation. Bergapten-loaded NLCs exhibited PS of 23.5 nm with 0.25 PDI confirming narrow size distributions, whereas blank NLCs showed 20.7 nm PS and 0.19 PDI. The ZP of bergapten-loaded NLCs was -13.0 mV which was found almost the same as blank NLCs. SEM images confirmed the smooth surface and spherical shape of NLCs. HPLC validated method for drug quantification was found simple and efficient. Successful fabrication of drug-loaded NLCs showed PS, PDI and ZP within range with smooth and spherical shape and HPLC methods showed good estimation of bergapten in NLCs.

Background: In 2019, a new unprecedented coronavirus, called SARS-CoV-2, emerged in Wuhan, China, rapidly spread from region to region, and became a global crisis. It has affected all dimensions of human life and has resulted in economic devastation and social anxiety in the world. Objective: The current study aimed at investigating the social-distancing compliance among pedestrians in Ahvaz city, the capital of Khuzestan Province, southwest Iran in summer 2020. Methods: This study was a cross-sectional descriptive research and was conducted from 2 to 11 August 2020. The data collection was performed based on the observation of passers-by in streets. A total of 5220 pedestrians were selected from eight urban districts and 92 neighborhoods of the city. \nResults: The overall compliance rate of social distancing was obtained equal to 16.3%. In addition, the highest rate of observance of social distancing was found in the 50-59-year-old age group (19.8%), while the lowest rate was seen in the participants aged under 10 years (5.5%). The lowest compliance rate of social distancing among pedestrians occurred at 17.00 o’clock (8.5%), while the highest rate occurred at 23.00 o’clock (30.8%). \nConclusion: The results also showed that the overall compliance rate of social distancing among the participants was very low and inefficient. This had made the control of the disease difficult and had directed Ahvaz to a critical situation in terms of coronavirus outbreak for several months. Considering the above-mentioned points, the findings of this study may assist health policymakers cope with the disease.

In the context of new emerging infectious diseases, it is more secure for old patients to be confined at their homes while still having medical assistance. Most existing facilities use Radio Frequency (RF) devices to monitor and measure vital signs of a patient and send them to appropriate medical services. But this technology can have bad effects on patient’s health, especially those who have already chronicle diseases. The approach we are proposing uses only LiFi as a standalone technology. Our goal is to use the information about the position of the patient in order to track him or her so that rapid intervention can be made in case of critical situation. The first experiments conducted on our system show that the patient can be tracked with precision. His /her real-time status is notified to medical services so that he/she can be rescued when needed.

This descriptive correlational study was carried out to determine the relationship between epistemological beliefs and utilization of information technologies in individuals of different generations. The study was conducted with 781 people who voluntarily accepted to participate in the study. The persons to be sampled from each generation were determined by random sampling method. Data were collected using an Information Form, the Utilization of Information and Communication Technologies Scale, and the Epistemological Belief Scale. The SPSS windows program was used to analyze the data. The Utilization of Information and Communication Technologies Scale total mean score was significantly lower in silent generation than in all other generations; in baby boomers than in generations X, Y and Z; in generation X than in generations Y and Z; and in generation Z than in generation Y (p<.05). In addition, the Epistemological Beliefs Scale total mean score was significantly lower in generation Y than in all other generations (p<.05). There was no significant relationship between the utilization of information technologies and epistemological beliefs in individuals of all generations (p<.05). In line with the results obtained in this study, training on information technologies should be prepared, carried out and evaluated considering that each generation has a different tendency to learn. In addition, educational activities such as seminars, workshops and meetings can be organized in order to enable individuals to review their perspectives on epistemological beliefs in accordance with specific characteristics of each generation.

Deoxyribonucleic acid (DNA) is coding proteins in its parts named genes. DNA and protein are both macromolecules, which are formed up of linear polymeric chains. Those chains are composed of unit structures. The variation in the unit structures of the DNA is less than that of the proteins. However, 3 consecutive unit structure of DNA code for one unit structure of protein. Besides, there are non-coding regions in the genes, in case of eukaryotes. Therefore, information contents are not equal in the encoding genes and the encoded proteins. Here, Shannon’s entropy in the protein-coding (encoding) deoxyribonucleic acid (DNA) is equalized with the encoded protein.

The size of the virus is 20-100 times less than bacteria and it is the smallest in size and the most severe risk of viral diseases: such as Covid 19. By comparing maps of COVID-19, spreading in some countries and their climate maps ,it was observed that the climate impacts effect on the outbreak or spreading of COVID-19, showing different roles in different countries, in contrasting climatic regions that are desert or that are exposed to currents of electrically charged dust that have the ability to kill the Corona virus in the atmosphere and less spreading of COVID-19. Accordingly, COVID-19 can be intensified by cleaner regions and less prevalence in arid regions, while it can be completely mitigated by increasing these factors in a temperate zone. This finding could be useful for future research to identify key influencing factors to mitigate the COVID-19 outbreak. Two important cases have been studied in the spread of the Corona virus, such as China and Iran. it was found that the regions that are exposed to dust currents are less spreading of the coronavirus because the dust is composed of metal oxides when exposed to sunlight that work to produce electrons and active particles by photo reactions that work to kill the virus

The main goal of Multicasting is a beneficial use of available bandwidth. By using a single path between two or more than two nodes can enhance the efficiency and simplicity in the Multicast group. Through the capability of multicasting in a network, the communication cost in-network can reduce, and the network can save its resources by sending only one set of data for multiple receivers at a time. Multiple senders may transfer data to multiple receivers at the same time in any multicast groups; however, each sender node has its group members for receiving data through multicasting. Our research-based on Virtual Cord Protocol, we will implement Multicasting in Virtual Cord Protocol (VCP), which takes the benefits of Virtual Coordinates improved efficient routing and to manage data communication wirelessly. In the VCP network, all nodes are connected virtually and physically. There are two methods for finding a specific path for nodes and the second are associated data items. In the first case, VCP always moves towards the destination, and in the second case, the greedy routing is used for the communication of available local nodes. VCP can find them close to the shortest path. Moreover, the multicasting is not yet been implemented on DHT-based protocols.

Internet of things (IoTs) is one of the most emerging technologies nowadays. It has started to participate in almost every aspect of our social life, ranging from financial transactions to the healthcare system, communication to national security, battlefield to the smart homes, and so on. However, the wide deployment of IoTs suffers certain issues as well, such as interoperability, compatibility, heterogeneity. Among the others, security and energy efficiency are the most prominent challenges. The limited energy and computing resources (e.g. processing power, storage) of IoTs put hindrances on information sharing across edge or IoT network. Indeed, unintentional or malicious interference with IoT’s data may lead to severe consequences. In this study, we exploit the potential benefits of the blockchain system and integrate it with software-defined networking SDN while mitigating energy and security challenges. More specifically, we proposed a new routing protocol with the cluster structure for IoT network using blockchain-based architecture for the SDN controller. The proposed architecture obviates Proof-of-Work POW with private and public blockchains for Peer-to-Peer P2P communication between SDN controller and IoT devices. In addition to this, a distributed trust-based authentication mechanism makes blockchain even more adoptive for IoT devices with limited resources. The experimental results show that the cluster structure base routing protocol outperforms the state-of-the-art AODV, DSDV, SMSN, EESCFD, and AOMD, in terms of energy consumption, network throughput, and packet latency.

A non-destructive testing setup is developed using a 1 MHz ultrasonic transducer and tested for identifying the adulteration in milk. For this study we have used water, urea and sugar as adulterants. Ultrasonic velocity is measured for samples prepared with adulterants in milk. It is shown that ultrasonic velocity is varying with adulteration. Ultrasonic velocity obtained for pure milk, milk + 10% water + .25g/10ml of sugar and milk + 10% water + .25g/10ml of urea are 1522 m/s, 1527 m/s and 1529 m/s, respectively. The ultrasonic velocity of milk adulterated with sugar and urea shows higher ultrasonic velocity than pure milk with the same density values. This method can be used for online monitoring the quality of milk the in a large scale to avoid adulteration of milk.

This paper describes a more straightforward way of monitoring the irregularities of the track and updates it in the cloud. The track quality means estimated by the signal, which remains measured from the accelerometer. The abnormalities present in the rail track should be identified initially and rectify it for safe and smooth travel. In this paper, a cloud-assisted rail track monitoring system and an ensemble machine learning technique have proposed to monitor the condition of the track. The micro electro mechanical system (MEMS) accelerometers have used to measure the signal and which remained placed in the axle box. The global positioning system (GPS) remains used to locate the exact location of the abnormality. Initially, the data measurement subsystem has used to measure the railway track vibration signals, and a reception subsystem has used to send data to the server. The ensemble machine learning technique consists of feature extraction methods and a classifier. A novel mixed strategy has performed to ensure the effectiveness of the proposed method. Four distinct fault cases have considered, and the test result shows that the proposed ensemble machine learning technique provides better feature extraction and classification.

Objective: \nThis systematic review aims to identify factors associated with single-use plastic usage.\nMethods: \nFive electronic databases namely, Scopus, Embase, PubMed, Web of science and CINAHL were used to search from inception to April of 2020, for studies pertaining to the investigation of factors (i.e. knowledge, attitudes, practice) associated with single-use plastic usage.\nResults:\nFrom the five included studies, we found that younger generations and females had a more pro-environmental attitude and practices towards SUP while only youngsters were associated to high knowledge level. Results also showed that a high education level doesn’t necessarily result in good practices.\nConclusion: \nSingle use plastics pollution is a worldwide problem and most of us are aware of its impact on us, our environment and surrounding, however SUP reduction practices are still low. To remedy to this pressing situation, better interventions and more alternatives materials to plastics are needed. Furthermore, we need more people to adopt the sustainable attitude and behaviour to make a change.

Cellular metabolic changes triggered by Obstructive Sleep Apnea Syndrome (OSAS) are detected invasively by detecting isoprene as a biomarker of OSAS in the breath. When falling asleep, isoprene level begins to increase above 3 ppm. Therefore, monitoring isoprene levels in exhaled breath under normal conditions may provide a non-invasive method to detect, monitor, and control sleep disorders such as sleep apnea. Therefore, in this study, PSSA-g-PANI based SAW gas sensors were prepared and tested against isoprene gas. Sensor measurements reveal that PSSA-g-PANI based SAW type sensor detected (1-150) ppm isoprene gas in the 60s with high sensitivity. Sensor measurements reveal that a prepared PSSA-g-PANI based SAW type sensor may enable monitor and control of sleep apnea.

Let $\\Gamma=(V,E)$ be a connected graph of order $n$. An ordered subset $\\mathbb{D}$ of vertices in $\\Gamma$ is said to be a resolving set for $\\Gamma$, if all the vertices of $\\Gamma$ are uniquely determined by the vector of distances to the vertices in $\\mathbb{D}$. The metric dimension of $\\Gamma$ is the minimum cardinality of a resolving set $\\mathbb{D}$ and that resolving set is the metric basis for $\\Gamma$. In this work, we show that the metric dimension is three for four closely related families of convex polytopes.

A new pandemic disease named as novel corona virus disease (COVID-19) was discovered during end of 2019 in Wuhan city of China and was quickly spread throughout the globe. But, till now no medicine is available to fight against the infection caused by the disease. The infection may also be transmitted easily from person to person through highly infectious nasal droplets when a healthy person comes in contact with a distance of less than 1m from the affected person. The doctors, physicians as well as nurses consult the patients very closely to assess the health conditions of the affected persons and there is a great chance that they may carry infection from them. In this work, we have proposed an intelligent mask to assist COVID-19 patients/doctors/nurses with an innovative SensMask to address this issue. This mask contains GPS sensor, IR proximity sensor, walk sensor and FS5 sensor. All patients need to wear this mask to observe the health details. Such sensors monitor health data from patients and send it to the cloud through the home/hospital-based local cloudlet. The cloudlet information is used by physicians for further diagnosis of patients. This proposed approach was simulated and the results obtained indicate that it helps in maximizing throughput and reduced delay.

Context-aware computing refers to system ability to sense its environment and modify its behavior for delivering suitable services. Having such kind of systems with the Near Field Communication (NFC) capability, opens new perspectives and research areas, allowing very useful type of applications known as NFC-based context-aware applications. These systems require correctness due to their applicability and then need to be proven formally using exhaustive analysis approach such as formal verification. In literature, most of works focuses on creating a general model for context aware systems ignoring the specificity of certain applications such as NFC applications where they present a higher complexity. We emphasize the existence of little or no work in this area supporting formal modeling. To boost it, we propose BigNFC as a novel formal-model based on Bigraphical Reactive Systems (BRS) taking account the interaction mode from the beginning, so we establish mapping between BRS and BigNFC components, where the structures are modelled as bigraphs and behaviors as rewriting rules. Finally, to validate our model, we have applied it on a real-life application and some properties were checked successfully.

With the advancement in technology and population growth, the motivation of integrating utility grid with the microgrid through power electronic converters increases. This paper presents the control of power electronic converter connected at the grid side to regulate the power flow between renewable energy system, load and grid in addition to the compensation of harmonic and reactive power. The reference currents are generated to decide the power flow from RES to the load and to suppress the harmonic and reactive power in the grid making grid current sinusoidal. In this paper, the reference current generation techniques like instantaneous p-q method and extension p-q method are implemented and compared. Linear Quadratic Regulator (LQR) is used to track the reference current. The control law of LQR is designed in a simple way using simplified equivalent circuit of a three-phase grid integrated renewable energy system. The system is tested experimentally under balanced and unbalanced conditions in two different modes such as insufficient renewable power and excess renewable power. The supremacy of extension p-q method over instantaneous p-q method is proved by getting low total harmonic distortion and better power factor under balanced and unbalanced conditions experimentally.

This study mainly focuses to develop\na new similarity measure named as an improved cosine similarity measure (ICSM) for interval valued\nintuitionistic fuzzy sets (IVIFSs), which significantly enhances the strength of the relationship between two objects. According to the structure characteristic of such\nsimilarity measure, two submeasures are constructed to\nbuild a new similarity measure (ICSM). We construct\ntwo submeasures: First, when only the middle term of membership grade with existing cosine similarity measure (CSM). Secondly, when complement of both membership and non-membership grades with existing CSM. Then, the ICSM is computed by taking the\naverage of constructing measures and existing measure. Further, the properties of the proposed measure\nare verified and also compared with other existing measures. Finally, the proposed ICSM is implemented\nfor pattern recognition and multiple criteria decision making problems, which are to deliver to validate the\neffectiveness of the designed similarity scheme.

The research discusses the main features of the performance of folk instrumental music (FIM). In public concert Tripura conditions, it addresses different components of the FIM conducted. The research also examines the components historically recommended by FIM performers and the results provided by music in performances such as raga mood, tranquilly, scalability and astonishments. The purpose of this analysis is to identify the music elements that have a direct effect on the viewer. The study concentrates on the various elements of the rating of the audience. In order to collect data, the famous FIM festivals have been picked. The results basically reveal that sluggish improvisations and historically recognized raga moods are the high-impact components of the listeners\' good acceptance; the implementations of high-speed components often make the renderings excellent.

Solar rooftop power plants are more popular in India. But the installed capacity of the rooftop plant is not meet the load demand in practical. Conventional grids share heavy loads by using the control switch to meet the load demand. But the loads are not constant. Due to this, there is no proper utilization of rooftop solar Electric Power. Hence, a unique Power electronic converter system called Micro - flexible AC transmission system (M-FACTS) is proposed in this paper. Micro - flexible AC transmission system consist of the multi-port converter with bi-directional power flow controlling system which consists of some features of FACTS devices and a combination of DC boost converter. The DC battery and solar power can be regulated using a bi-directional buck-DC boost converter to maintain the DC bus constant. The main objective of this unique converter and control is to improve the better utilization of solar electric power and reduce the power consumption from the conventional electrical grid. Hence the rooftop solar electric power can be fully utilized all the generation time. Moreover, the proposed system provide reactive support and to store the excess solar electric power into the storage system. Mat lab -Simulink based simulation results proved the effectiveness of the efficient converter and the control system for the effective utilization of solar electric energy.

Picture fuzzy set is an efficient tool for dealing with uncertainty and vagueness, particularly in situations that require assimilation of more dimensions of linguistic assessment such as human voting, feature selection, etc. The correlation coefficient of picture fuzzy sets is a tool to determine the association of two picture fuzzy sets. It has several applications in various disciplines like science, engineering, and management. The prominent applications include decision-making, pattern recognition, clustering analysis, medical diagnosis, etc. In this paper, we introduce a new correlation coefficient for picture fuzzy sets with the justification of its advantages. This correlation coefficient is better than the existing correlation coefficients and other such measures in the picture fuzzy theory because it expresses the extent of association between two PFSs along with the nature of the association (positive or negative). Further, we examine the improvisation of the proposed picture fuzzy correlation coefficient over some existing picture fuzzy correlation measures in view of its application in pattern recognition. Finally, we utilize the proposed picture fuzzy correlation coefficient in solving a decision-making problem related to the identification of a suitable COVID-19 mask.

Feeder-bus route network configuration (FBRNC) is a simple form of an intermodal transportation system, which involves the provision of access to an existing mainline movement (rapid transit system) through a feeder transit system (bus) usually to increase the service coverage of the mainline service. In this study, a simple strategy is developed to solve this problem by first clustering demand nodes (bus stops) around nearest destination (train station), using genetic algorithm based on fixed start multiple salesman problems to optimize the shortest distance that covers the entire service area, evaluation of performance characteristics, and consequently using Pareto front to select the best scenario. Four scenarios were generated (2, 3, 4, 5, salesperson) by using a genetic algorithm and Pareto efficient solutions ensued. Scenarios of 5-salesperson, 3-salesperson together with Kuah and Perl, 1989 solution lies on the non-dominated solution front 1 while 2 and 4-salesperson that are equally good solution forms the second non-dominated solution front. The 3-salesperson scenario has the overall minimum total cost and hence represents the best solution. The developed strategy can be used to design feeder bus routes.

New methods for studying of the anomalous magnetic field of the lithosphere and modeling of the sources of anomalies in different layers of the Earth\'s crust are given in this article. The interpretation consists of three stages: separation of anomalies from the sources in different layers of the Earth\'s crust, data conversion to the magnetic pole and solving of the inverse problem of finding the surface of sources. The new computer algorithms were created using parallel computing in the multiprocessor computer systems. To demonstrate the developed methods, we chose the region of Eastern Europe 300 km × 230 km, where the large magnetic anomalies are located. Anomalies from various layers of the Earth\'s crust were identified and the models of the sources of magnetic anomalies in the granite layer and the surface of the basaltic layer were constructed. The study revealed basic-ultramafic massifs under a thick sedimentary cover, as well as extended deep belts and large elevations of the basalt layer of the Earth\'s crust. The results clarify the lithosphere structure of the Western Urals (Russia) and can be used for geodynamic reconstructions.

Voice Recognition System (VRS) for deaf peopleis proposed to be operated through the voice Commands of a human for deaf impairment people. The goal of this system is to listen voice commands and show text. This system act on the voice commands received from the normal user. The text would perform its operations based on the voice commands given by a human. Deaf people would analysis the text of the voice commands. There is not much work done in voice signals analysis for deaf impairment people, so this research could have a good success. The scope of this research of Voice Recognition System (VRS) for Deaf people.So that people can experience faster analysis text through voice commands. The people with deaf impairment will be able to analysis this.The main purpose of this project is to design and implement a user-friendly system to interconnect between the deaf and normal person. This project uses the speech processing to convert voice into text. This work will help in improving the communication with the deaf and normal people.

Vehicular ad-hoc networks (VANETs) are mobile networks intended to connect vehicles to provide secure communication among the vehicles. In this direction, many researchers worked on establishing secure communication in VANETs. However, due to network openness, still VANETs are facing potential issues related to security and privacy. In this paper, we proposed a secure communication system for VANETs with privacy, which consists of Enhanced privacy preserving mutual authentication procedure for safe communication in V2V, and, deriving a session key using vehicle identities, time stamps and the secret values(nonce) shared during the session. Further, we compared the proposed technique with existing techniques and satisfactory results were obtained in favor of the proposed in terms of less computation. Finally, a formal security model is established to secure against unknown key share attack, replay attack, key-compromised impersonation attack etc.

Lot streaming, which has attracted much attention in recent years, is an effective technique to increase production efficiency in a productive system by splitting a job into several smaller parts to overlap operations between successive machines in a multi-stage production system. In the other hand, the limitations of buffer capacity and the impact of the learning effect have not been considered in a lot-streaming hybrid flow shop scheduling problem. In this paper, a bi-objective hybrid flow shop scheduling problem with lot streaming, learning effect and buffer\'s limitation are considered. For solving the problem, a mathematical model is aimed to minimize the total tardiness and the makespan is presented. Since the problem is NP-hard, NSGA-II and NRGA algorithms were considered to solve it. Experimental results show that the NRGA performs much more effectively for the problem.

The interest in selecting the most appropriate Cloud data center to execute the users’ requests is usually area of interest due to the fact of incremental and continuous growth of users’ requests which might pose different challenges to the Cloud sector. The curse of challenge is presented in the Cloud data center selection problem by ever-increasing users’ requests required to be executed and the number of data centers required to be selected to execute these requests. Thus, the selection of the Cloud data center, which has been performed by Cloud Service Broker policy, is a case of NP-hard problem that needs a precise solution that provides an efficient superior solution. Differential evolution algorithm is a metaheuristic algorithm, which is characterized by its fastness and robustness as well. In this paper, a modified Differential Evolution algorithm-based Cloud Service Broker policy is presented to select the most proper data center in the Cloud Computing environment. A refined Differential Evolution algorithm by a new mutation technique is proposed, which ensures enhanced performance and provides a more efficient selection of data centers. The superiority of the proposed policy is evaluated and demonstrated by selecting the cloud data centers using the CloudAnalyst simulator and the results are compared with state-of-arts Cloud Service Broker policies.

Digital image processing and retrieving have increasingly become very popular on the Internet and getting more attention from various multimedia fields. That results in additional privacy requirements placed on efficient image matching techniques in various applications. Hence, several searching methods have been developed when confidential images are used in image matching between pairs of security agencies, most of these search methods either limited by its cost or precision. This study proposes a secure and efficient method that preserves image privacy and confidentially between two communicating parties. To retrieve an image, feature vector is extracted from the given query image, and then the similarities with the stored database images features vector are calculated in order to retrieve the matched images based on an indexing scheme and matching strategy. We used a secure content-based image retrieval features detector algorithm called Speeded-Up Robust Features (SURF) algorithm over public cloud to extract the features and the Honey Encryption algorithm. The purpose of using the encrypted images database is to provide an accurate searching through encrypted documents without needing decryption. Progress in this area helps protect the privacy of sensitive data stored on the cloud. The experimental results (conducted on a well-known image-set) show that the performance of the proposed methodology achieved a noticeable enhancement level in terms of precision, recall, F-Measure, and execution time.

We show that some open problems in computational complexity can be solved by advanced proof theoretic techniques. In particular, consider the well-known complexity classes NP, coNP and PSPACE. It is known that NP and coNP are contained in PSPACE, but a more precise characterization of these relationships remained open until [2], [3] (also [4]) presented proofs of the equalities NP = coNP = PSPACE. These results were obtained by the novel proof theoretic tree-to-dag compressing techniques to be explained in this paper in more detail.\n\n[2] L. Gordeev, E. H. Haeusler, Proof Compression and NP Versus PSPACE, Studia Logica (107) (1): 55-83 (2019)\n\n[3] L. Gordeev, E. H. Haeusler, Proof Compression and NP Versus PSPACE II, Bulletin of the Section of Logic (49) (3): 213-230 (2020)\nDOI: https://doi.org/10.18778/0138-0680.2020.16\n\n[4] L. Gordeev, E. H. Haeusler, Proof Compression and NP Versus PSPACE II: Addendum, arXiv:2011.09262 (2020), to appear in Bulletin of the Section of Logic.

Two generalized identities are established to obtain midpoint and\ntrapezoidal inequalities for convex function with respect to strictly monotone function. These inequalities provide corresponding results for convex, harmonic convex, p-convex and geometrically convex functions. Also some new inequalities can be generated via specific strictly monotone functions.

Large semigroups and groups of transformations of finite affine space of dimension n with the option of computability of the composition of n arbitrarily chosen elements in polynomial time are described in the paper.Constructions of such families are given together with effectively computed homomorphisms between members of the family. These algebraic platforms allow us to define protocols for several generators of subsemigroup of affine Cremona semigroups with several outputs. Security of these protocols rests on the complexity of the word decomposition problem, It allows to introduce algebraic protocols expanded to cryptosystems of El Gamal type which are not a public key system. In particular symbiotic combination of these protocol of Noncommutative cryptography with one time pad encryption is given Some of these nonclassical multivariate cryptosystems are implemented with platforms of cubical transformations.

AI adoption behavior requires firms’ preparedness, zeal, and high management support. Technology describes that adoption is influenced by the pool of technologies internal and external to the firm as well as their perceived usefulness, technical and organizational compatibility, and learning curve, pilot test/ experimentation, and visibility/imagination (Awa et al., 2015a, b). The research provides a more holistic picture about adoption success factors, the foreseeing challenges; the technology’s impact on organizational excellence and post-adoption benefits. The research adopts the descriptive analytical approach in addition to using resources of data collection of both primary and secondary resources. Primary resources used mixed data collection instruments of both questionnaires and interviews. Secondary sources included literature review in the relevant books, references, periodicals, research papers and previous studies. The research sample draws from Turkish private business sector firms in health care, education, marketing and advertising organizations, services outlets, financial organizations, general trading & commerce institutions and telecommunications firms.\nStructural equation modeling is applied to analyze the data. A total of 11 factors are proposed to influence AI adoption critically. The results show that four factors, namely compatibility, managerial support, and observability directly affect AI adoption. Organization’s technical capability and perceived relative advantage impact compatibility, but they are indirectly related to AI adoption. Competitive pressure impacts relative advantage of AI technologies, but it is indirectly related to AI adoption. However, the empirical results in this study indicate that trialability factor is not related to AI adoption. It should be noted that this factor might still exert influence in other situations. Based on the main study, the additional study tests the role of external environment factors and finds that although some of them are not critical determinants for AI adoption, some of them can influence compatibility, which indicates that the external environment factors are still significant in the whole adoption process. \nAlthough the research doesn’t purport to capture all factors that affect AI adoption and firm sustainable growth, and the findings could be further examined by future research, it provides a good understanding and valuable framework within which to develop and test empirical propositions in the related sectors. Secondly, similar researches could be conducted elsewhere outside the geographical scope of this research, including additional variables so as to validate the findings of this research.

The software Randentropy is designed to estimate inequality in a random system where several individuals interact moving among many communities and producing dependent random quantities of an attribute. The overall inequality is assessed by computing the Random Theil\'s Entropy. Firstly, the software estimates a piecewise homogeneous Markov chain by identifying the changing-points and the relative transition probability matrices. Secondly, it estimates the multivariate distribution function of the attribute using a copula function approach and finally, through a Monte Carlo algorithm, evaluates the expected value of the Random Theil\'s Entropy. Possible applications are discussed as related to the fields of finance and human mobility.

Recognizing a person based on the biological features are increasing nowadays. Biological aspects are static features fixed as a primary key for distinguishing the people group. A perfect image with perfect colour and intensity must be considered as an input. Though numerous images are taken by the video camera, an average de-noised image is selected for the Segmentation process. Image Segmentation process segments the image into clusters so as to reduce the complexity of the image and hence makes the image analysis easier. The average de-noised image from the list are found using Frame differencing method. The wavelet transform method is used to detect the edges of the average image. Using the histogram of the image, the image details are highlighted. The difference between the white and gray values of the image pixels are used to calculate the gradient value. The gradients are calculated in all the four directions without missing the edge points. In this work, Binarization and Top-bottom Agglomerative clustering hierarchy (BTTBACH) is proposed for building hierarchy of clusters by considering each data point in the input image. Then the clusters are paired and merged to make a single cluster containing all the data points of the clusters. The proposed cluster hierarchy methods performs well with less computing time than structural or stochastic methods. The quality of segmented image is measured by comparing the parameters such as CDR, FAR, FRR, PSNR, Jaccard Similarity Coefficient and Dice coefficient.

Product identification using barcodes has gained wellrepute especially at the point of sale where different products werebeing scanned individually before making the payment receipt.these products when at the warehouse where individual scandemand lots of time and labor to be involved in that process andabove all, there is always a chance of human error. Barcodes havebeen in a process of replacement by Radio Frequency Identification(RFID). RFID is a technology that enables data transfer wirelesslyand provides an advantage over barcodes, where the line of sight isneeded. Much of the work has been done on RFID tag antennadesign, but efficient reader antenna design is a major need of bigwarehouses, that came across bulk data to manage on daily basis.RFID reader antennas are not able to focus their RF energy to aparticular zone. This paper proposes an energy-efficient RFIDreader antenna design that utilizes the RF energy efficiently to meetthe bulk reading application that will help in managing the taggedstock for the purpose of warehouse management.

In recent years, the Internet of Things (IoT) has become an important technology for connecting various smart objects in many applications, especially in health monitoring applications. The IoT technology develops healthcare applications from traditional to personalized ones by making the treatment and monitoring of patients more easily. Nowadays, especially during the COVID-19 pandemic, the necessity of enhancing the healthcare monitoring applications to avoid the spreading of this pandemic is increased. In this paper, a mechanism is proposed to minimize the direct contact with COVID-19 patients who need the ventilators by using IoT technology. The proposed mechanism saves the medical providers from the COVID-19 infection and then minimizes the spreading of this disease.

Novel approaches under the extreme conditions of ultra-high gravity of a massive black hole allow us to assume that spacetime degrades into the one dimension of time. A unique interpretation of the non-relativistic Schrödinger equation together with the relativistic Klein-Gordon and Dirac equations is presented by swapping the three dimensional space derivatives with the singular time derivative in the D’Alembertian operator. This interpretation reveals a unique wave equation that results in some extraordinary implications such as time quantization with the intervals of around 3.36 zs which is in the order of uncertainty in time, ∆t=1.3 zs, calculated from the energy-time version of the Heisenberg uncertainty principle for electrons. As a result of this time quantization, an antisymmetric wave function around the edge of the event-horizon zone appears and indicates that the virtual particle-antiparticle pairs of the electron field split into two real components with the spin-up and down states, reconfirming the Hawking radiation. Energy eigenvalues calculated from the application of the Dirac equation consolidates the preservation of energy and charge. The wave equation invoked in this study reduces into the time dependent Dirac equation within the neighborhood of zero-point, t=0, insuring the relevance of the evaluations.