Search

Nowadays, the unmanned aerial vehicle (UAV) has a wide application in transportation. For instance, by leveraging it, we are able to perform accurate and real-time vehicle speed detection in an IoT-based smart city. Although numerous vehicle speed estimation methods exist, most of them lack real-time detection in different situations and scenarios. To fill the gap, this paper introduces a novel low-altitude vehicle speed detector system using UAVs for remote sensing applications of smart cities, forging to increase traffic safety and security. To this aim, (1) we have found the best possible Raspberry PI’s field of view (FOV) camera in indoor and outdoor scenarios by changing its height and degree. Then, (2) Mobile Net-SSD deep learning model parameters have been embedded in the PI4B processor of a physical car at different speeds. Finally, we implemented it in a real environment at the JXUST university intersection by changing the height (0.7 to 3 m) and the camera angle on the UAV. Specifically, this paper proposed an intelligent speed control system without the presence of real police that has been implemented on the edge node with the configuration of a PI4B and an Intel Neural Computing 2, along with the PI camera, which is armed with a Mobile Net-SSD deep learning model for the smart detection of vehicles and their speeds. The main purpose of this article is to propose the use of drones as a tool to detect the speeds of vehicles, especially in areas where it is not easy to access or install a fixed camera, in the context of future smart city traffic management and control. The experimental results have proven the superior performance of the proposed low-altitude UAV system rather than current studies for detecting and estimating the vehicles’ speeds in highly dynamic situations and different speeds. As the results showed, our solution is highly effective on crowded roads, such as junctions near schools, hospitals, and with unsteady vehicles from the speed level point of view.

This study deals with identifying the accident blackspots and the influencing factors causing accidents using factored analysis in a medium-sized city (Tirunelveli) in India. From the literature review, the geospatial technique to identify the blackspots and the factors causing accidents was used for analysis. The most influencing factors driving the accidents were identified and ranked based on the repetitive occurrence of accidents in the blackspot area. The spearman ranking system showed the correlation among the factors causing accidents. The factor analysis technique was utilized to identify the key factors driving the repetitive accidents and group them. This study will help transportation planners understand the factors causing accidents and take appropriate measures to reduce the casualties in the road construction planning stage and existing conditions.

Melasma is a chronic and acquired pigmentary condition that primarily affects women and undermines patient satisfaction and confidence. Melasma mostly affects females, accounting for 90% of all cases. It affects people of all races, particularly those with skin types IV and V who live in areas with lots of UV radiation. According to the studies, Melasma lesions are seen throughout the face in centrofacial, malar, and mandibular patterns. Melasma lesions on the forehead, cheeks, nose, upper lip, and/or chin are the most prevalent centrofacial pattern. Melasma lesions can also be detected along the periorbital area, especially in Asian people. Melasma is notably resistant to treatment, with many patients experiencing only temporary relief and relapses. Combining therapies that target numerous pathologic components, including photodamage, inflammation, aberrant vascularity, and abnormal pigmentation, generally results in the most dramatic therapeutic improvements. Treatments for dark circles include topical depigmenting medicines like hydroquinone, kojic acid, azelaic acid, and topical retinoic acid, and physical treatments such as chemical peels, surgical adjustments, and laser therapy. The objective of therapy should be to figure out what is causing the hyperpigmentation and what is contributing to it. This article provides an overview of melasma therapies and the efficacy of methimazole and cysteamine for melasma therapy.

The Internet of Things (IoT) has been considered in various fields in the last decade. With the increasing number of IoT devices in the community, secure, accessible, and reliable infrastructure for processing and storing computed data has become necessary. Since traditional security protocols are unsuitable for IoT devices, IoT implementation is fraught with privacy and security challenges. Thus, blockchain technology has become an effective solution to the problems of IoT security. Blockchain is an empirical data distribution and storage model involving point-to-point transmission, consensus mechanism, asymmetric encryption, smart contract, and other computer technologies. Security and privacy are becoming increasingly important in using the IoT. Therefore, this study provides a comprehensive framework for classifying security criteria based on blockchain technology. Another goal of the present study is to identify causal relationship factors for the security issue using the Fuzzy Decision-Making Trial-and-Evaluation Laboratory (FDEMATEL) approach. In order to deal with uncertainty in human judgment, fuzzy logic is considered an effective tool. The present study’s results show the proposed approach’s efficiency. Authentication (CR6), intrusion detection (CR4), and availability (CR5) were also introduced as the most effective and essential criteria, respectively.

Vague incidence graph (VIG), belonging to the FG family has good capabilities when facing with problems that cannot be expressed by FGs. When an element membership is not clear, neutrality is a good option that can be well-supported by a VIG. The previous definitions limitations in connectivity concept have led us to offer new definitions in VIGs. Hence, in this paper, the VIG and its matrix form are proposed. Vague incidence subgraph (VISG) is defined with several properties. Incidence pairs, paths, and connectivities between pairs in VIGs are introduced. Likewise, different types of strong and cut pair in VIGs are examined with their properties. Universities are one of the most important centers for human education and play an important role in the development of the country. But the point to be very careful is that the employees of a university must do their job in the best possible way. Therefore, we have tried to identify the most effective person in a university according to its performance by presenting an application.

Atopic dermatitis (AD) is a chronic skin disease that may be triggered by psychological conditions and several allergens. Patients with AD may be experienced disease exacerbation due to the COVID-19 pandemic lifestyle including home-quarantine and increased stress. We obtained the electronic data of 100 AD patients admitted to our hospital from 2016 to 2019 and called them with specific phone line.Out of 100 patients, 43 were male, and 57 were female (mean age±SD: 45.85±16.90). Sixty patients (37 females and 23males; mean age: 42.22±14.71) confronted disease flare-up during the COVID-19 era. Exacerbation of AD was correlated with treatment dose alteration, a lengthy history of atopic dermatitis, eczema duration, self-isolation, frequent handwashing, hand disinfection, and POEM scoring (P

The publisher's final version of this work can be found at https://doi.org/10.1049/cds2.12138. Deposited by shareyourpaper.org and openaccessbutton.org. We've taken reasonable steps to ensure this content doesn't violate copyright. However, if you think it does you can request a takedown by emailing help@openaccessbutton.org.

The concept of convex ordered hyperrings associated with a strongly regular relation was investigated in this study. In this paper, we first studied hyperatom elements of ordered hyperrings and then investigated characterizations of quotient ordered rings. Is there a strongly regular relation θ on a convex ordered hyperring R for which R/θ is a convex ordered ring? This leads to an ordered ring obtained from an ordered hyperring.

BACKGROUND In the modern world, mobile applications are essential to human advancement and pandemic control is no exception. The use of mobile applications and technology for the detection and diagnosis of COVID-19 disease has been the subject of numerous investigations. Objective: Since no thorough analysis of the COVID-19 epidemic prevention has been done using mobile applications. Due to this gap, the current study thoroughly covers the many uses of mobile applications for COVID-19 detection and diagnosis. OBJECTIVE Since no thorough analysis of the COVID-19 epidemic prevention has been done using mobile applications. Due to this gap, the current study thoroughly covers the many uses of mobile applications for COVID-19 detection and diagnosis. METHODS A search of five major research databases (ScienceDirect, Scopus, PubMed, Web of Science, IEEE) found 535 studies, among which 42 related to the diagnosis and detection of patients suspected of having COVID-19. RESULTS Mobile applications can be categorized into five areas based on the content of these studies: contact tracing, data gathering, data visualization, artificial intelligence-based methods, rule- and guideline-based methods, and data transformation. Patients with COVID-19 have been identified using mobile applications employing a variety of clinical, geographic, demographic, radiological, serological, and laboratory data. The majority of studies concentrated on using artificial intelligence (AI) methods to identify people who might have COVID-19. Additionally, compared to other data types, symptoms, cough sounds, and radiological images were used more frequently. CONCLUSIONS Mobile applications could soon play a significant role as a powerful tool for data collection, epidemic health data analysis, and early identification of suspected cases. These technologies can work in conjunction with the Internet of Things (IoT), cloud storage, 5G, and cloud computing.

In this paper, first, we state an operator LR on an ordered semihyperring R. We show that if φ:R⟶T is a monomorphism and K⊆R, then LT(φ(K))=φ(LR(K)). Afterward, hyperatom elements in ordered semihyperrings are defined and some results in this respect are investigated. Denote by A(R) the set of all hyperatoms of R. We prove that if R is a finite ordered semihyperring and |R|≥2, then for any q∈R{0}, there exists hq∈A*(R)=A(R){0} such that hq≤q. Finally, we study the LR-graph of an ordered semihyperring and give some examples. Furthermore, we show that if φ:R⟶T is an isomorphism, G is the LR-graph of R and G′ is the LT-graph of T, then G≅G′.

Bleomycin is an antineoplastic agent, which is used off label for various dermatologic conditions. There are numerous reports on the use of intralesional bleomycin (ILB) for the treatment of common warts. However, reports on the efficacy of bleomycin in the treatment of anogenital warts (AGWs) are still limited. The aim is to compare the efficacy/tolerability and recurrence rates of AGW treatment with ILB versus cryotherapy. In this prospective study, 50 patients with AGWs were assigned either to receive triple freeze–thaw cycle of cryotherapy or to receive 1.5 mg/mL ILB for a maximum of four sessions with 3-week intervals. Clinical efficacy was determined by the percentage of the patients with complete clearance. The patients with complete clearance were visited by passing 3 months from the last treatment session to evaluate any recurrence. Of 44 patients completing the study, 16 of 21 (76.19%) patients in the ILB group and 15 of 23 (65.22%) patients in the cryotherapy group showed complete resolution ( p value = .425). Moreover, recurrence occurred after 3 months in 18.75% and 46.66% of the ILB and the cryotherapy groups’ patients, respectively ( p value = .096). The most common local adverse events in both treatment groups were pain, dyspigmentation, and ulceration/erosion, while the delayed ulceration and secondary infection were only observed in the bleomycin group. Intralesional bleomycin is as effective as cryotherapy in the treatment of AGWs, but it is more invasive and associated with post-treatment pain, the delayed ulceration, and cutaneous infection. Intralesional bleomycin is not accompanied with the major risk of necrosis or fibrosis, so the use of ILB in the anogenital area is likely to be safe. This clinical trial was registered in Iranian Registry of Clinical Trials site with code: IRCT20190519043631N1.

Background: Few studies have evaluated patients’ motivations for seeking minimally invasive cosmetic procedures. Objective: This study aimed to assess the demographic characteristics and motivation of patients who seek minimally invasive cosmetic procedures in two academic referral dermatology centers. Methods: The study included adult patients seeking minimally invasive facial cosmetic procedures at two academic dermatology centers in Tehran, Iran, between January 2019 and June 2019. Results: The majority of patients were married, employed women with a mean age of 39.6 ± 10.74 years. The most common region of the face they expected to change was the eyes (56%). Patients who requested fillers desired their cheeks to improve significantly more than patients who requested toxin injections (20.5% vs. 3%; p = .005). Patients had mostly heard about the procedures from friends (40.4%). Approximately one third of patients had experienced a major life event during the preceding year (loss of a family member [50%], marriage [26.9%]). A minority of patients had ever visited a psychiatrist (13.9%), and 15.3% had a history of using psychiatric drugs. The procedure type requested by men was significantly different from that requested by women (88.2% vs. 60.8 % for Botox; 11.8% vs. 34.9% for fillers, and 0% vs. 4.3 % for fat injections; p = .044). The most common motivating factor for patients was gaining rejuvenation (39.2%). The most common preventive factors for patients to undergo the procedures earlier were financial issues (41.7%). Conclusion: Patients seeking minimally invasive cosmetic procedures were married, educated, employed women in their 30s desiring rejuvenation and commonly were not influenced by external factors, such as relationships or the media.

This paper deals with identifying the accident black spots and the influencing factors causing accidents using factored analysis in the medium-sized city (Tirunelveli) in India. From the literature review, the geospatial technique to identify the black spots and the factors causing accidents was used for analysis. The most influencing factors driving the accident were identified and ranked based on the repetitive occurrence of accidents in the black spot area. The spearman ranking system obtained the correlation among the factors causing accidents. The factor analysis technique was utilized to identify the key factors driving the repetitive accidents and group them. This study will help transportation planners to understand the factors causing accidents and take appropriate measures to reduce the casualties in the road construction planning stage and existing conditions.

The Internet of Things (IoT) is a self-configuring, intelligent system in which things connect to the Internet and communicate with each other. As “things” are autonomous and rely on a significant amount of autonomy to carry out their individual and collective tasks, it is possible that the autonomous environment of IoT may raise privacy concerns. IoT encounters significant privacy and security challenges, including inaccurate device updates, a lack of efficient privacy solutions, user unawareness, and famed active device monitoring capabilities. In this paper, the authors describe the background of IoT systems and privacy and security measures, (a) approaches to preserving privacy in IoT-based systems, (b) existing privacy solutions, and (c) recommending privacy models for different layers of IoT applications. Based on the results of our study, it is clear that new methods such as Blockchain, Machine Learning, Data Minimization, and Data Encryption can greatly impact privacy issues to ensure security and privacy. Moreover, it makes sense that users can protect their personal information easier if there is less data to collect, store, and share by smart devices. Thus, the use of Data Minimization methods in these networks can be very beneficial for privacy-preserving, which is useful to route researchers to

Artificial intelligence techniques are excessively used in computing for training, forecasting and evaluation purposes. Among these techniques, artificial neural network (ANN) is widely used for developing prediction models. ANNs use various Meta-heuristic algorithms including approximation methods for training the neural networks. ANN plays a significant role in this area and can be helpful in determining the neural network input coefficient. The main goal of presented study is to train the neural network using meta-heuristic approaches and to enhance the perceptron neural network precision. In this article, we used an integrated algorithm to determine the neural network input coefficients. Later, the proposed algorithm was compared with other algorithms such as ant colony and invasive weed optimization for performance evaluation. The results reveal that the proposed algorithm results in more convergence with neural network coefficient as compared to existing algorithms. However the proposed method resulted in reduction of prediction error in the neural network.

Keratosis lichenoides chronica (KLC) is a rare dermatosis which represents different clinical characteristics between adult‐ and pediatric‐onset cases. We described a childhood case of KLC with features typical for adult‐onset disease. Acitretin led to partial improvement of her skin, but not mucosal, lesions., Keratosis lichenoides chronica (KLC) is a rare dermatosis which often manifests in adults and less commonly in childhood. Although its manifestation in children is described to be distinct from that of adults, its presentation could be analogous in both.

Osteoma cutis (OC) or cutaneous ossification refers to uncommon bone formation in the skin. Primary OC develops without any predisposing factor or pre-existing lesion, whereas secondary OC sets out as a dystrophic ossification following traumatic, cicatricial, and neoplastic factors or other cutaneous inflammations. Herein, we report a rare case of long-standing progressive primary OC of the scalp resected in 3 sessions with no recurrence after 1 year.

Data is generated over time by each device in the Internet of Things (IoT) ecosphere. Recent years have seen a resurgence in interest in the IoT due to its positive impact on society. However, due to the automatic management of IoT devices, the possibility of disclosing sensitive information without user consent is high. A situation in which information should not be unintentionally disclosed to outside parties we do not trust, i.e., privacy-preserving. Additionally, IoT devices should share their data with others to perform data aggregation and provide high-level services. There is a trade-off between the amount of data utility and the amount of disclosure of data. This trade-off has been caused a big challenge in this field. To improve this trafe-off efficiency rather than current studies, in this study, we propose a Privacy-Preserving Data Aggregation architecture, PPDMIT, that leverages homomorphic paillier encryption, K-means, a one-way hash chain, and the Chinese Remainder Theorem. We have found that the proposed privacy-preserving architecture achieves a more efficient data aggregation than current studies and improves privacy preservation by utilizing extensive simulations. Moreover, we found that our proposed architecture is highly applicable to IoT environments while preventing unauthorized data disclosure. Specifically, our solution depicted 8.096% improvement over LPDA and 6.508% over PPIOT.

Automated guided vehicles (AGVs) are popular subsets of robots that come in various shapes and sizes. The group’s use in the industry ranges from applications for carrying pallets, carts, and utensils to helping the elderly or transporting medicine to hospitals. Even recently, they have been used in libraries to carry books on shelves. The main part of an AGV includes its body, motor, driver, processor, and sensors, which are more or less the same in all types of AGVs, and addons vary depending on the application and the work environment. The part that affects AGV performance is the control strategy, to which researchers have shown different approaches. Using various techniques and simulations to obtain a model is the key and can help to improve and evaluate the performance of the strategy of the robot. In this study, based on the actual design of the AGV system, all data and components are described, and the simulation is performed in MATLAB software. Then, for controlling the platform based on the PID controller tuning, four methods of Ziegler Nichols, empirical, Particle Swarm Optimization (PSO), and Beetle Antennae Searching (BAS) (optimizer) are discussed, and the results are compared in the four paths including the circle, ellipse, Spiral and 8-shaped paths by observing and testing the tuned PID parameters. Finally, a series of subsequent experiences were carried out in CoppeliaSim (VREP) as a famous robot simulator to overcome the environmental constraints for the same paths that were used in Matlab based on the extracted PID values. Based on the results, the empirical methods, PSO, and BAS errors are very close together. But in general, the BAS algorithm is the fastest, and the PSO had better performance. In general, the maximum error is linked to the path of 8 shapes and the minimum is related to circle shape one. Finally, the analysis of results in different paths in both simulators shows the same results. Therefore, concerning the limited test on the real platform and using the PID coefficients obtained from the simulation shows the model’s ability for the researchers in robotic research.

Background Subcision, also known as subcutaneous incisionless surgery, is a surgical intervention used to treat a variety of skin conditions including atrophic acne scars, depressed scars, cellulite, and wrinkles. Aims We plan to prepare a review article about the indications of subcision, its adverse reactions, and pearls. Patients/methods We searched the literature for the information about subcision and its applications from papers published up to March 2019. The search was performed through the databases of the National Library of Medicine. Results After a thorough review of the published papers about subcision, we finally chose to review 40 articles that had proper sample size and design to prepare this review article. Twenty-one papers were related to the application of subcision in the treatment of acne scar and other scars. Four articles were about the application of subcision to treat cellulite, and eight articles were related to other applications of subcision such as the treatment of striae or nasolabial fold. The remaining seven articles include published review papers about subcision or acne scar classification. Conclusion Subcision seems to be effective on various skin conditions including acne scar, other depressed scars, and cellulite. It is easy to apply and inexpensive with short downtime and no significant complications. Subcision needs proper technique and adequate experience.

We report two cases of lichen planus following COVID-19 vaccination in two middle-aged women, where the first patient presented with lichenplanopilaris (LPP) relapse and development of lichen planus 14 days after the second dose of AstraZeneca vaccine, and the other patient who had a previous scattered lesion of LP which extended and increased in severity after the first and second dose of Sinopharm. The suggested cause could be due to immune dysregulation and up regulation of T cell lymphocytes which was triggered after COVID-19 vaccination. What supports our hypothesis that LP had occurred due to COVID-19 vaccination, is that one of the patients responded successfully to Metronidazole. This means that the infection process after vaccination could be the cause in aggravating LP. To add, one of the suggested mechanisms for the appearance of LP or reactivation of a dormant LPP can be cytotoxic CD8 T-lymphocytes which increase the secretion of IFN-γ and IL-5 cytokines and may also result in basal keratinocytes' apoptosis leading to cutaneous manifestations. This was supported by the efficacy of Tofacitinib that was used in the other patient who presented with reactivation of LPP in addition to LP. Tofacitinib decrease the number of T cell infiltration and adjust IFN expression.

Stress is the response or a change in our bodies to environmental factors like challenges or demands that are physical and emotional. The main cause of stress is illnesses and it is gaining more interest, a hot topic for many researchers. Stress can be brought about by a wide range of normal life occasions that are hard to avoid. Stress generally refers to two things: first, the psychological perception of pressure and the body’s response to it. On the other hand, it involves multiple systems, from metabolism to muscles to memory. Many methods and tools are being developed to reduce stress in humans. Stress can be a short-term issue or a long-term problem, depending on what changes in your life. The emphasis of this article is to reduce the effects of stress by developing a stress-releasing game and verifying its results through the Profile of Mood States (POMS) and POMS-2 survey. Games are associated with stress levels; hence, parameters like sounds, visuals, and colors associated with reducing stress are used to develop a game for the stress reduction in the players. The survey research aims to determine that the purpose-built game will affect the player's stress level using a reliable psychological survey paper. The survey collected a variety of information from its participants over six months. Different aspects of a person’s psychology and reactions are recorded in this scenario by calculating the mean, standard deviation, degree of freedom, zero-error, and probability-value%. The POMS and POMS-2 results are obtained from the custom-built game, and these are found to be effective in reducing stress.

Machine learning as a service (MLaaS) plays an essential role in the current ecosystem. Enterprises do not need to train models by themselves separately. Instead, they can use well-trained models provided by MLaaS to support business activities. However, such an ecosystem could be threatened by model extraction attacks—an attacker steals the functionality of a trained model provided by MLaaS and builds a substitute model locally. In this paper, we proposed a model extraction method with low query costs and high accuracy. In particular, we use pre-trained models and task-relevant data to decrease the size of query data. We use instance selection to reduce query samples. In addition, we divided query data into two categories, namely low-confidence data and high-confidence data, to reduce the budget and improve accuracy. We then conducted attacks on two models provided by Microsoft Azure as our experiments. The results show that our scheme achieves high accuracy at low cost, with the substitution models achieving 96.10% and 95.24% substitution while querying only 7.32% and 5.30% of their training data on the two models, respectively. This new attack approach creates additional security challenges for models deployed on cloud platforms. It raises the need for novel mitigation strategies to secure the models. In future work, generative adversarial networks and model inversion attacks can be used to generate more diverse data to be applied to the attacks.

In this study, we propose the concept of left extension of a hyperideal by generalizing the concept of k-hyperideals in ordered semihyperrings with symmetrical hyper-operation ⊕. By using the notion of extension of a k-hyperideal, we prove some results in ordered semihyperrings. The results of this paper can be viewed as a generalization for k-ideals of semirings.

The problems of Internet stability, heterogeneity, fairness of bandwidth sharing among streams, efficiency of use and congestion control have been solved in this article. This paper proposes an improved scheme of TCP proxy acknowledgement based on Automatic Repeat Request (ARQ), which improves throughput, reduces delay and saves uplink bandwidth of wireless link, and is more suitable for future asymmetric networks. The substantial improvement is observed during the experimentation as processing efficiency of protocol. The observed results revealed that overall processing time for each packet is approximately equals to one fourth of the transfer control protocol and the reduction of 59% is also observed in the utility of resources. The protocol also incorporates various simple techniques for the recovery of loss to improve the throughput in noisy wireless conditions. The results show that the adoption of the average diversity combining technology is helpful to improve the throughput and effective factor performance, and can reduce the requirement of radio link protocol (RLP) maximum retransmission times. As nearly 90% of uplink acknowledgement frames are filtered, the uplink bandwidth utilization rate is significantly improved. Decomposing large data frames into small data frames is also helpful to improve system performance.

The Publisher's final version can be found by following the DOI link. Data quality plays a crucial role in the context of smart buildings. Meanwhile, missing data is relatively common in acquired datasets from sensors within the smart buildings. Poor data could result in a big bias in forecasting, control and operational services. Despite the common techniques to handle missing data, it is essential to systematically select the most appropriate approach for such missing values. This paper aims to focus on the lift systems as one of the essential parts in the smart buildings by exploring the most appropriate data imputation methods to handle missing data and to provide its service and allow a better understanding of patterns to issue the correct control actions based on forecasted models. The imputed data is not only investigated statistically but also modelled through machine learning algorithm to explore the impact of selecting inappropriate imputation techniques. Seven imputation techniques deployed on datasets with three level of missing values including 10%, 20% and 30% and the performance of methods examined through the normalized root mean square error (NRMSE) approach. In addition, the interaction between imputation techniques and a machine learning algorithm, namely random forest were examined. Findings from this paper can be employed in identifying an appropriate imputation technique not only within the lift datasets, but smart building context.

Power transformers being among the power system key components, are very important to protect. Various approaches have so far been proposed for this topic. Artificial intelligence (AI) has provided a concrete basis for numerous power transformer differential protection methodologies. However, the capabilities of AI-based methods have never been put into comparison. This paper provides a comparative analysis of various AI-based approaches for differential protection of power transformers. The performances of AI-based differential protection schemes are investigated in the presence of current transformer (CT) saturation condition, series capacitors compensation, and superconductor fault current limiter (SFCL), which possibly deteriorate the capability of differential protections to correctly tell inrush currents and internal faults apart. The PSCAD/EMTDC simulation tool is applied in producing the necessary test dataset for performance evaluation of the suggested novel strategy. The attained outcomes from the assessment of various methods have been analyzed to introduce the most superior AI-based differential protection scheme.

Background The management of melasma is still challenging, and new treatment modalities with favorable side effect profile are required. Methimazole, a peroxidase inhibitor, seems to have a beneficial effect in the management of melasma but there is a paucity of studies for evaluation of its efficacy. This double-blinded trial was aimed to evaluate the efficacy and safety of methimazole vs hydroquinone 4% which is the gold standard treatment in the management of melasma. Methods Fifty patients with melasma were enrolled and randomly divided into two groups to receive 4% hydroquinone or 5% methimazole once daily for 8 weeks. Forty patients completed the study. The clinical response was assessed at 4th, 8th, and 12th weeks after treatment by MASI score, patient satisfaction, and physician scores. Results Both groups showed a reduction in the MASI score at the 8th week which was more significant in hydroquinone group but higher relapse rate was also observed in this group after discontinuing the drug. The side effects were similar between groups. Also, patient and physician satisfaction scores were also more in favor of hydroquinone 4%. Conclusion Methimazole could be an alternative treatment of melasma alone or in combination with other depigmenting drugs. Although not as effective as hydroquinone, the noncytotoxic and nonmutagenic aspects of methimazole may make it a promising alternative for the treatment of melasma.

Nowadays, wireless mesh networks are known as important parts of different commercial, scientific, and industrial processes. Their prevalence increases day-by-day and the future of the world is associated with such technologies for better communication. However, the issue of improving quality of service for dealing with more complex and intense flow of data has been always a remarkable research problem, as a result of improved wireless communication systems. In this sense, objective of this study is to provide a new algorithm for contributing to the associated literature. In the study, peer to peer wireless mesh networks and the concept of service quality were examined first and then an approach for improving service quality in such networks has been proposed accordingly. In detail, the proposed an approach allows profiting data transfer capability by data packet and using this information for routing and preventing overcrowd in network nodes and finally, distributing the load over it. When middle nodes overcrowd, they withhold to send control messages of route creating or do that by delay. The proposed approach has been evaluated and the findings revealed that at least 10% of undue delays through network can be prevented while permittivity does not reduce, thanks to the approach. Also energy consumption within network nodes partially increases due to adding table and the search which can be overlooked.

Background: The World Wide Web houses an abundance of information that is used every day by billions of users across the world to find relevant data. Website owners employ webmasters to ensure their pages are ranked top in search engine result pages. However, understanding how the search engine ranks a website, which comprises numerous web pages, as the top ten or twenty websites is a major challenge. Although systems have been developed to understand the ranking process, a specialized tool based approach has not been tried. Objective: This paper develops a new framework and system that process website contents to determine search engine optimization factors. Methods: To analyze the web page dynamically by assessing the web site content based on specific keywords, elimination method was used in an attempt to reveal various search engine optimization techniques. Conclusion: Our results lead to conclude that the developed system is able to perform a deeper analysis and find factors which play a role in bringing the site on the top of the list.

Stakeholder satisfaction is the main motive of the software industry. Consumer and producer satisfaction means achieving a software-quality product. There are so many techniques, methods, and models are present for the software-quality prediction. Computational intelligence is also playing a crucial role in the prediction of quality characteristics. This paper gives a new optimal mathematical model for the prediction of the degree of stakeholder satisfaction (Q). Optimal models validate the real data using the relationship impacts of various quality attributes. It uses the equations of constraints. The optimal model gives the maximum and minimum values for Q. Constraints constitutes of software quality characteristics. In the given case study example, the idle value of Q is 30 but using optimal model it gives the maximum optimal value of Q = 22.788020075 for xLAB IT consulting services on their project In-Reg Molecule Registration using the MATLAB. It means if there is any change in the value of any software quality characteristics, then it will decrease the value of Q. It proves that the given result is an optimal solution.

Limitations of the pinhole method and astigmatic defocus detection have difficulties in determining the direction of defocus and a restricted linear correction range. Here, a distance-measuring approach based on the laser triangulation principle is proposed with a corresponding mathematical model to overcome these problems and to satisfy the requirements of an industrial thin-film transistor liquid-crystal display (TFT-LCD) inspection microscope system in active auto-focus applications. The approach combines infrared light at a wavelength of 808 nm with visible light. The light reflected from the surface of the object reaches a CCD camera and forms a spot via a set of optical devices. To control a PZT to achieve real-time auto-focusing, a Gaussian curve fitting method is used to process the spot information with the presented mathematical model giving the relationship between the detection value and the defocus value focus error signal (FES). The preliminary experiments with a $50\times $ objective lens show that the measured values are consistent with the theoretical values, have good linearity and possess a focusing accuracy of 0.2 $\mu \text{m}$ within $\pm 30~\mu \text{m}$ of the focal plane. The analysis of the experimental results proves the feasibility of using this method in industrial applications. Compared with the traditional method of microscope focus correction, this method has the advantages of high accuracy, good linearity, and fast focus speed for the actual requirements of industrial inspection processes. This method has been applied to the circuit board component defect detection in our laboratory.

Recently, IoT has greatly influenced our daily lives through various applications. One of the most promising application is smart city that leverages IoT devices to manage cities without any human intervention. The high possibility of sensing and publishing sensitive data in this smart environment leads to three significant issues: (1) privacy-preserving (2) heterogeneity, and (3) real-time services. We observe that current studies are in lack of addressing these challenges. In this paper, we propose a new privacy-preserving architecture for IoT devices in the smart city by leveraging ontology, a data model, at the edge of the network. At first, we propose an ontology that consists of privacy information of devices. Then, we mount a real-time privacy-preserving method on top of it that is achieved by providing a dynamic environment from the privacy-preserving point of view. Based on the simulation results using Protege and Visual Studio on a synthetic dataset, we find that our solution provides privacy at real-time while addressing heterogeneity issue so that many IoT devices can afford it. Thus, our proposed solution can be widely used for smart cities.