فهرست مطالب s. m. razavi

The recognition of facial expressions using metaheuristic algorithms is a research topic in the field of computer vision. This article presents an approach to identify facial expressions using an optimized filter developed by metaheuristic algorithms. The entire process of feature extraction hinges on using a filter optimally configured by metaheuristic algorithms. Essentially, the purpose of utilizing this metaheuristic algorithm is to determine the optimal weights for feature extraction filters. Once the optimal weights for the filter have been determined by the metaheuristic algorithm, optimal filter sizes have also been determined. As an initial step, the k-nearest neighbor classifier is employed due to its simplicity and high accuracy. Following the initial stage, a final model is presented, which integrates results from both filterbank and Multilayer Perceptron neural networks. An analysis of the existing instances in the FER2013 database has been conducted using the method proposed in this article. This model achieved a recognition rate of 78%, which is superior to other algorithms and methods while requiring less training time than other algorithms and methods.In addition, the JAFFE database, a Japanese women's database, was utilized for validation. On this dataset, the proposed approach achieved a 94.88% accuracy rate, outperforming other competitors. The purpose of this article is to propose a method for improving facial expression recognition by using an optimized filter, which is implemented through a metaheuristic algorithm based on the KA. In this approach, optimized filters were extracted using the metaheuristic algorithms kidney, k-nearest neighbor, and multilayer perceptron. Additionally, by employing this approach, the optimal size and number of filters for facial state recognition were determined in order to achieve the highest level of accuracy in the extraction process.

Team performance is one of the ways to deal with successive changes from the point of view of experts. Therefore, continuous changes in the work environment and daily work activities require sharing ideas and the need for continuous learning and entrepreneurship. Neglecting entrepreneurship has a negative effect on companies and by neglecting entrepreneurship, it is impossible to operate effectively in a dynamic environment. Therefore, in today's competitive world, companies will lose their competitiveness. Thus, the purpose of this study is to investigate the effect of team performance on the internationalization of digital startups through mediating role of entrepreneurship. In terms of the purpose, it is applied and quantitative research. The research population is estimated to be 375 employees of 101 Iranian international digital startups in the field of technology and city services, which accounted for 10% of exports between 2021 and 2022. The sample size is estimated through Cochran's formula of 190 people. To collect data, a standard 5- point Likert scale questionnaire with 22 items was used. Finally, the data were analyzed by using Smart PLS 3 software. The results showed that emotional commitment, creating an environment of innovation, and knowledge sharing through mediating role of entrepreneurship have a positive and significant effect on the internationalization of digital startups.  The results of the research indicate positive relationships among Emotional Commitment (2.671) and with entrepreneurship mediating (2.927), Innovative environment (2.478) and with entrepreneurship mediating (2.697), and Knowledge sharing (2.707) and with entrepreneurship mediating (3.333) concerning the internationalization of digital startups. Therefore, these hypotheses were confirmed. The team performance of employees plays an important role in the survival and success of companies in the international sector. The knowledge that companies gain from other companies, especially during internationalization, can escalate their competitiveness in the global market. The performance of the team as the primary factor of learning and innovation facilitates trust among the company's employees.

Deterrents are materials that use in gun propellant formulations as controlling initial burning rate and to prevent of high chamber pressures in the interior ballistic. However, traditional deterrents are highly toxic and suspected carcinogen which makes them chemicals of concern that are non-energetic inert compound and reduce total chemical energy of propellant and reduce final performance of it. Modifying a propellant formulation via replacement current deterrent, can have a marked effect on the toxicity and corrosiveness of the combustion products, the rate of energy release and the cleanness of burning. Using of nitrogen rich energetic materials with low burning rate as new deterrents can improve burning properties of propellant without reduce total energy content.

Power amplifier is one of the main components in the RF transmitters. It must provide various stringent features that can lead to complicating the design. In this paper, a new optimizing method based on the inclined planes system optimization algorithm is presented for the design of a discrete power amplifier. It is evaluated in a 2.4-3 GHz power amplifier, which is designed based on “Cree’s CGH40010F GaN HEMT”. The optimization goals are input and output return losses, Power Added Efficiency, and Gain. Large signal simulation of the optimized power amplifier shows a good performance across the bandwidth. In this frequency range, the input and output return losses are about lower than -10 dB, the Power Added Efficiency is greater than 51%, while the Gain is higher than 13.5 dB. A two-tone test with a frequency space of 1 MHz is applied for the linearity evaluation of the designed power amplifier. The obtained result shows that the power amplifier has good linearity with a low memory effect.

Stock markets have a key role in the economic situation of the countries. Thus one of the major methods of flourishing the economy can be getting people to invest their money in the stock market. For this purpose, reducing the risk of investment can persuade people to trust the market and invest. Hence, Productive tools for predicting the future of the stock market have an undeniable effect on investors and traders’ profit. In this research, a two-stage method has been introduced to predict the next week's index value of the market, and the Tehran Stock Exchange Market has been selected as a case study. In the first stage of the proposed method, a novel clustering method has been used to divide the data points of the training dataset into different groups and in the second phase for each cluster’s data, a hybrid regression method (HHO-SVR) has been trained to detect the patterns hidden in each group. For unknown samples, after determining their cluster, the corresponding trained regression model estimates the target value. In the hybrid regression method, HHO is hired to select the best feature subset and also to tune the parameters of SVR. The experimental results show the high accuracy of the proposed method in predicting the market index value of the next week. Also, the comparisons made with other metaheuristics indicate the superiority of HHO over other metaheuristics in solving such a hard and complex optimization problem. Using the historical information of the last 20 days, our method has achieved 99% accuracy in predicting the market index of the next 7 days while PSO, MVO, GSA, IPO, linear regression and fine-tuned SVR has achieved 67%, 98%, 38%, 4%, 5.6% and 98 % accuracy respectively. in this research we have tried to forecast the market index of the next m (from 1 to 7) days using the historical data of the past n (from 10 to 100) days. The experiments showed that increasing the number of days (n), used to create the dataset, will not necessarily improve the performance of the method.

Drinking water supply in the household consumption sector has always been emphasized due to its direct impact on human health. One of the common methods to reduce soluble solid pollutants that is used in many parts of the country, is the use of household water purifiers. Despite the usefulness of filters in these devices which need to be replaced at regular intervals, they waste 70-80% of piped water by transferring it to sewage due to their mechanism of action based on reverse osmosis. In contrast, there are solar distillation systems that produce distilled water using solar energy. The use of solar distillation systems has a high potential to provide quality drinking water for sparsely populated areas and hot weather due to its prevention of water loss, easy use and long life. The purpose of this research was to Techno-economic study the use of household water purifiers and solar distillation system to achieve quality and potable water in homes, as well as to analyze the sensitivity of water cost, operating cost and increase the initial fixed cost. The results show that despite the higher initial cost of the solar distillation system, the cost of using these systems in the long run is more economical, and the water loss for these systems can be ignored.

In this paper, a new structure of the SiC metal-semiconductor field effect transistor (SiC-MESFET) is presented. In the proposed structure of the upper part of the channel under the gate, a semiconductor with very low impurity density is used and at the bottom of the channel, a semiconductor with a high impurity density is used. The most important electrical characteristics of the proposed transistor such as breakdown voltage, drain current, threshold voltage, electric field and gate capacitor are simulated and compared with these characteristics in conventional transistor. According to the simulation results, the proposed structure reduces the maximum electric field in the channel and thus increases the breakdown voltage from 127 V to 136.5 V compared to the conventional structure. The new structure also increases the saturation drain current by 30% compared to the conventional structure. The high density of impurities in the channel bottom causes a negative shift in the threshold voltage in the provided transistor. According to the obtained results and increasing the drain current and the breakdown voltage, the proposed transistor can be used in high power applications.

There are two serious issues regarding gait recognition. The first issue presents when the walking direction is unknown and the other one presents when the appearance of the user changes due to various reasons including carrying a bag or changing clothes. In this paper, a two-step view-invariant robust system is proposed to address these. In the first step, the walking direction is determined using five features of pixels of the leg region from gait energy image (GEI). In the second step, the GEI is decomposed into rectangular sections and the influence of changes in the appearance is confined to a small number of sections that could be eliminated by masking these sections. The system performs very well because the first step is computationally inexpensive and the second step preserves more useful information compared to other methods. In comparison with other methods, the proposed method shows better results.

Stock price prediction has become one of the interesting and also challenging topics for researchers in the past few years. Due to the non-linear nature of the time-series data of the stock prices, mathematical modeling approaches usually fail to yield acceptable results. Therefore, machine learning methods can be a promising solution to this problem.

In this paper, a novel machine learning approach, which works in two phases, is introduced to predict the price of a stock in the next day based on the information extracted from the past 26 days. In the first phase of the method, an automatic clustering algorithm clusters the data points into different clusters, and in the second phase a hybrid regression model, which is a combination of particle swarm optimization and support vector regression, is trained for each cluster. In this hybrid method, particle swarm optimization algorithm is used for parameter tuning and feature selection.

The accuracy of the proposed method has been measured by 5 companies’ datasets, which are active in the Tehran Stock Exchange market, through 5 different metrics. On average, the proposed method has shown 82.6% accuracy in predicting stock price in 1-day ahead.

The achieved results demonstrate the capability of the method in detecting the sudden jumps in the price of a stock. The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.

The Markov random field (MRF) theory has been accepted as a highly effective framework for designing noise-tolerant nanometer digital VLSI circuits. In MRF-based design, proper feedback lines are used to control noise and keep the circuits in their valid states. However, this methodology has encountered two major problems that have limited the application of highly noise immune MRF-based circuits. First, excessive hardware overhead that imposes a great cost, power consumption and propagation delay on the circuits and second, separate implementation of feedback lines that adds further delay to the circuits. In this paper, we propose a novel approach for minimal-cost inherent-feedback implementation of low-power MRF-based logic gates. The simulation results, which are based on 32nm BSIM4 models, demonstrate that besides excellent noise immunity of the proposed method, it has the least propagation delay in comparison with all of the previously reported MRF-based gates due to its inherent feedbacks. In addition, the proposed method outperforms competing ones, which have comparable noise immunity, in other circuit metrics like cost and power consumption. Specifically, the proposed method achieves at least 18%, 29%, and 39% reductions in cost, delay and power consumption with considerable noise immunity improvement compared with competing methods.

The huge amount of data created constantly with increasing rate from different sources such as smart phones, social media, imaging technologies and etc. becomes difficult to be analyzed by conventional data analytic tools. For this reason a new field of research called Big Data Analytics is growing faster in the research and industrial communities. Clustering big datasets is one of the important challenges which attracts more and more attentions among researchers. In this paper first a method for non-automatic big data clustering (when the number of clusters is known) and then a two-stage method for big data automatic clustering (able in finding the number of clusters) based on grey wolf optimization algorithm are introduced.  In the first stage the algorithm tries to find the number of clusters using a tree structure and in the second stage the main algorithm searches the solution space to find the position of centroids. The methodology is tested on 13 synthetics and 2 real big mobility datasets. The achieved results show its effectiveness in big data clustering.

Mobile crowd sensing is a new paradigm that uses the data sensed by mobile users to extract population data and then provides people-centered services. However, most users do not tend to participate voluntarily in this process. Therefore, availability of incentive mechanisms is mandatory to encourage users’ participation. In this paper, based on users-submitted data, a score-based incentive mechanism is proposed. This mechanism measures data quality via obtained contextual information from user data, and accordingly, gives score to the user. The fuzzy inference system is used in the center of the incentive mechanism to calculate the score. The proposed mechanism is evaluated via simulation and the effect of each parameter on the score acquired by user is shown. Simulation results show that this mechanism could be helpful in solving the problem of price imbalance in different areas of measurement and also is able to collect high-quality data at each measurement point with few number of participants.

Various studies have been conducted to show the effects of essences and enzymes on foodborne pathogens in culture media. The aim of this study was to determine the effect of Zataria multiflora Boiss. essential oil and lysozyme alone and in combination on preventing growth of Vibrio parahaemolyticus in culture media. In this study, the MIC of Zataria multiflora Boiss. essential oil and lysozyme, together and alone, on Vibrio parahaemolyticus, was determined by using macro and microdilution methods. The MIC of Zataria multiflora essential oil determined 0.01% and 0.02% by using macro and microdilution methods, respectively and lysozyme at 1000 mg/mL concentration could not inhibit the growth of V. parahaemolyticus. According to the results of current study, Zataria multiflora essential oil showed better results in comparison with lysozyme, moreover Applying lysozyme and essential oil together did not decrease MIC, but extended the latent phase of V. parahaemolyticus, which considered an important factor in microbiology.

Annually millions of Muslims depart to Saudi Arabia for performing a religious pilgrimage called "Hajj". In this ceremony, pilgrims face numerous health hazards and injuries such as pressing in overcrowding, sliding, burning, fal­ling down, traffic accidents etc. The main purpose of this study was to determine the prevalence of injuries in Hajj period across 2004 to 2008. This study was conducted on 253808 Iranian pilgrims on five consecutive years of Hajj ceremonies, from 2004 to 2008. We used a report sheet with 13 types of injuries and 13 mechanisms of these injuries. SPSS V13.5 soft ware was used for analyzing the data. ANOVA and independent sample t- test was conducted, and relationships were considered signifi­cant at P< 0.05. The most common injuries was "tissue contusions and ruptures "(about 76/10000), and "tendon lesions" (about 62/10000). In addition, the most common mechanism of injuries was "ankle sprain" (69/10000) during the five consecu­tive years. The prevalence of all fractures was about 49/10000 and the proportion of burning with hot water or fire was about 40/10000. Changes of all causes of the injuries were significant in this study (P< 0.05). We have suggested some directions for preventing of injuries and related Injuries in Hajj, in this study.

The aim of this study was to investigate the influences of various treatments with filter-aids materials on the quality and color indices of the Malas variety of pomegranate juice. Different materials used in the cold clarification method were pectolitic enzyme, pectolitic enzyme-gelatin-bentonit, pectolitic enzyme-gelatin-silica sol, pectolitic enzyme-gelatin-bentonit-silica sol, gelatin-bentonit, gelatin-silica sol; gelatin-bentonit-silica sol. Clarification methods significantly (P< 0.05) affected the color values of the pomegranate juices. The pectolitic enzyme-gelatin-bentonit-silica sol treatment was superior in clarity (%T660=91.80), pectin content (6.06g/100g-1), viscosity (33.97%) and had the lowest value of the Degradation Index (1.03) in comparison with other treatments (P<0.05). The resulting juice had no adverse changes in pH, brix, acidity and total anthocyanin content (TAC) (loss 20.81%) which are important quality indices in the fruit juice industry. Also, this treatment was the most effective method to reduce the browning index (53.7%), polymeric color (40.85%), Anthocyanin Color (20.35%) and Tanin Color (35.63%) values. Finally, pectolitic enzyme (120ppm)-gelatin (300ppm)-bentonit (200ppm)-silica sol (500ppm) treatment was suggested as an effective treatment for classic clarification of the pomegranate juice.

Nowadays Clinical Skills Centers are important structural components of medical education systems globally. In these centers medical students are trained using a variety of methods and techniques, one method being teaching in structured stations. The objective of this study was to determine the efficacy of this method by comparing the student's self-assessment of their own basic surgical skills before and after structured stations teaching. This quasi-experimental study was conducted in 2004-08 in Tehran University of Medical Sciences. The participants included 268 medical students at the clerkship stage; there were 3 trainer groups. The pre- and post-self assessment techniques were used to assess the learning progress. ANOVA & Paired-t and non-parametric tests were used for data analysis. Irrespective of which year the students were in, self- scoring on 17 cognitive subjects and 10 procedural skills showed a significant improvement after the instruction (p<0.001). There were significant differences among the 3 trainer groups (p<0.001). This study suggests that teaching basic surgical skills using structured stations is effective in improving practical skills.

Cryptosporidium a zoonotic parasite with various hosts is well recognized as pathogen in humans particularly those with immune-suppression or immune-deficiency. The epidemiologic considerations for cryptosporidiosis emphasize on transmission of resistant oocystes via drinking water vegetables food etc. The present study was undertaken to study the Cryptosporidium contamination in lettuce from different regions as a source of infection for human beings in Shiraz. In a deh1ive–analytical study the cryptosporidium contamination of 200 lettuce samples from four different rigions was investigated during spring and summer 2006. All samples were processed and examined using modified Ziel-Neilsen staining and also by a quantitative method for counting oocystes per sample. From a total of 200 samples forty seven samples (23.5%) were positive. No significant difference was seen between contamination rate of lettuce and seasons except for samples from Jahrom where showed higher contamination rate in spring than summer. In addition no significant difference was observed among oocytes count in different samples except for lettuce from Ahwaz in summer with higher parasite intensity. Regarding to the high contamination of lettuce with Cryptosporidium as well as to sanitary washing of vegetables before consumption taking special procedures appear to be helpful for reducing the contamination rate at the farm level.

Temporomandibular Joint (TMJ) is an important and complicated joint in the body with a critical role in chewing and speech. Some 50% to 60% of people are said to have a kind of disorder in their TMJs. Among those, 5%-10% suffer from acute or chronic dislocation of TMJ.The definitive treatment for this problem is surgery which of course has probable side effects such as ankylosis and facial nerve injury. Also, Routine conservative treatment just subside symptoms for a period of time. In this study, we evaluated if autologous blood injection in TMJ can be an acceptable conservative treatment for TMJ dislocation. This was a case-control experimental study including 10 rats. The right side TMJs formed the case and the left ones were considered as the control group samples. They were divided into 5 groups so that each group consisted of 2 rats. The groups were sacrificed on days 1, 3, 7,14 and 28. Both of TMJs on every individual were prepared for histological study. Fibrosis was assessed via digital imaging. The collected data were then statistically analyzed by SPSS statistical software using Wilcoxon test.(α = 0.05) The amount of fibrosis in the case group was statistically higher than in the control group (45.95% versus 34.44%) Blood injection into TMJ seems to be a simple and cost-effective therapeutic choice for patients with recurrent TMJ dislocation.

Schwannoma or Neurilemoma is a benign neoplasm of the nervous system originating from Schwann cells. It develops from the neural sheath of peripheral motor, sensory, sympathetic, and cranial nerves except for the optic and the olfactory nerves which basically lack Shwann cell sheaths. Approximately 25% to 45% of the schwannomas occur in the head and neck region. Usually, the mass is asymptomatic, though tenderness or pain is reported in some instances. Tongue is the most common site for oral neurilemomas. Occasionally, the tumor arises centrally within the mandibular bone and thus makes jaw expansion.Case Report: A 22-year-old man presented with a mass in the right side of his mouth floor allegedly existing from six months earlier. The mass was surgically removed. Sample sections of the mass were prepared. In microscopic examination with H&E, there were two areas of wavy and spindle cells within a loose and myxomatous stroma compatible with the known Antoni A and B patterns of Schwannoma. The tumor cells showed a diffuse positive immunohistochemical reaction to S-100 which supported the diagnosis. Schwannoma is a benign soft tissue tumor which mostly involves tongue within oral cavity. This tumor rarely occurs in other regions such as mouth floor.

Odontogenic Keratocyte is an evolutionary odontogenic cyst with an invasive nature and high recurrence rate. In this study, expression of bcl-2, the index for apoptosis inhibition was traced in OKCs via immunohistochemical assay. Expression of ki-62, the antigen indicating cellular proliferation was also checked similarly. The Tunel method was applied to look for apoptosis. The collected data were then compared to those of ameloblastomas to gain a better understanding of OKCs.

This was a cross-sectional, analytic and retrospective study. Sixteen samples of OKCs alongside a similar number of paraffin embedded solid ameloblastomas (SAB) already fixed in formalin were studied. The conventional Biotin-Streptavidin immunohistocheical assay was used to recognize through Tdt-mediated dutp biotin nick end TUNEL labeling. The collected data were then analyzed via independent and paired t-test on a computer using SPSS software.

Bcl-2 positive cells in the basal layer of OKCs (97.69% + 1.2) significantly outnumbered similar cells (53.01% + 18.57) in the peripheral layer of SABs (p value < 0.0001). The population of ki-67 positive cells in the suprabasal layer of OKCs (13.59 ± 7.47%) was obviously greater than in any other layers. It was especially higher than in the peripheral layer of SABs (7.38% ± 6.94). Although the population of ki-67 positive cells were larger in OKCs than in SABs, the difference did not prove significant (p value = 0.211) TUNEL positive cells in the peripheral layer of OKCs (7.69% ± 2.6) was significantly higher than in the deeper layers of SABs (1.95% ± 0.38).

The invasive nature and the high recurrence of OKCs, compared to SABs, seems to be due to the high proliferate activity of suprabasal cells rather than long cellular survival in the peripheral layers. Of course apoptosis in the superficial layers of OKCs seems to counteract the high proliferative activity of the deeper layers of ameloblastomas. As a result, OKCs maintain the same epithelial thickness quite contrary to ameloblastomas forming a solid tumoral mass.

Statement of problem: 

Oral lichen planus (OLP) is an immunologic mucocutanous disorder. Many factors such as stress, diabetics, HCV, Trauma and hypersensitivity have been introduced as its predisposing factors. Recently, much attention has been paid to the relationship between HCV and OLP.

According to different specifications of the virus in different races and geographic conditions, the purpose of this study was the assessment of the presence of HCV in oral lichen planus lesions.

We prepared 43 paraffin blocks (29 from OLP and 14 from normal oral mucosa). The OLP blocks were selected from the archive of Pathology department, dental faculty, Esfahan University of Medical Science. After preparing H & E slides from the paraffin blocks, diagnosis of the lesions was confirmed by a pathologist. Then, all the samples were examined by PCR for HCV genome. The data were analyzed using SPSS software and Fisher's Exact test with Pvalue of 0.05.

Among 43 samples examined, 3 were positive and 26 negative in the OLP group and all the 14 samples belonging to the normal mucosa were negative.

According to this study, there was no significant correlation between the presence of Hepatitis C virus genome and OLP lesions (p>0.05). So, researches on other viruses that are effective in oral diseases with more cases and also doing PCR on the blood and serum of OLP patients are recommended.

This article aims at identifying effective variables of macroeconomic on Tehran Stock Exchange returns. Variables which have been used to do the hypothesis test are Interest Rates, Interest Rates growth, GOP, GOP growth, Oil Prices and growth of Oil Prices. These variables have been considered as independent variables. The stock market return has been used as dependent variable. The measurement scope is over the period 1376-1385. The research shows that stock market return is relative to only interest rate.

To examine the problem of internet addiction within the perspective of consumers· personality, behavior and demographic characteristics.

This cross-sectional study was performed using 3 questionnaires, including Young's scale to measure the degree of tendency towards internet addiction and Mayer's - Briggs Type indicator (MBTI)• which has four dimensions for personality- and Dean's Alienation Scales (DAS) to measure alienation. There were a total of 732 respondents, aged 15 to 39 years. Responses were analyzed using factor analysis, analysis of variance, and multiple regression techniques.

Thirty percent of the respondents were addicted to the internet and showed various degrees of alienation, a sense of being powerless, isolated, introverted or excessively emotional.

It is essential to organize educational programs and counseling services to decrease internet addiction within Iranian families.

Multiple myeloma is a malignancy of plasma cells which affect the jaws in 15-30% of the cases. This paper explains a case of the multiple myeloma and its diagnosis.Case Report: The patient was 70 years old; he complained from painful nodule in the mandible interfered in chewing. In clinical examination some nodules were seen in the skull and jaws. In radiographic examination multiple destructive lesions were seen in the skull and jaws. The differential blood count (CBC diff), the urine analyzes, and biopsy was done. The diagnosis was multiple myeloma. More examinations and treatment process were done by oncologist. Although this is rare that the first signs of multiple myeloma are in the mouth and a patient comes to the dentist for diagnosis, but knowledge of the signs of this malignancy leads to fast diagnosis and treatment and improving the life time and the quality of life.

Use of glass ionomer cement as pit and fissure sealant, has added benefit by its fluoride-releasing property. The efficacy of using invasive and non-invasive techniques was assessed by microleakage of Glass ionomer (Triage, G C Corporation, Tokyo, Japan) and Resin based sealants (Concise, 3M Dental Products, USA).Methods and Materials: In this in vitro experimental study, 80 sound premolars were divided into four groups of 20. In groups 1 and 2, Triage and in groups 3 and 4, Concise was used. In groups 1 and 3, fissures leaved intact (Noninvasive technique). In groups 2 and 4, fissures were prepared with tapered diamond bur (Invasive technique).The teeth were thermocycled at 5o-55oc for 250 cycles and immersed in 5% methylene blue solution for 24 hours. Sectioned samples were observed for the extent of dye penetration, and scores were based on established scoring criteria. 0- Without dye penetration.1- Dye penetration restricted to the outer half of the sealant.2- Dye penetration restricted to the inner half of the sealant.3- Dye penetration into the underlying fissure.The data were analyzed using Kruskall-Wallis and Man-Whitney tests. There were no statistically significant differences between invasive and noninvasive techniques; but microleakage of Triage was statistically more than Concise. Because there was no difference between the two techniques, invasive technique is not recommended. Considering the recent controversies, it can be said that Triage cannot be a viable alternative for resin based sealants.