Distance-based clustering methods categorize samples by optimizing a global criterion, finding ellipsoid clusters with roughly equal sizes. In contrast, density-based clustering techniques form clusters with arbitrary shapes and sizes by optimizing a local criterion. Most of these methods have several hyper-parameters, and their performance is highly dependent on the hyper-parameter setup. Recently, a Gaussian Density Distance (GDD) approach was proposed to optimize local criteria in terms of distance and density properties of samples. GDD can find clusters with different shapes and sizes without any free parameters. However, it may fail to discover the appropriate clusters due to the interfering of clustered samples in estimating the density and distance properties of remaining unclustered samples. Here, we introduce Adaptive GDD (AGDD), which eliminates the inappropriate effect of clustered samples by adaptively updating the parameters during clustering. It is stable and can identify clusters with various shapes, sizes, and densities without adding extra parameters. The distance metrics calculating the dissimilarity between samples can affect the clustering performance. The effect of different distance measurements is also analyzed on the method. The experimental results conducted on several well-known datasets show the effectiveness of the proposed AGDD method compared to the other well-known clustering methods.

1Pulses form stable dietary components for majority of population across the world. different people consume pulses in different ways like Uncooked, Soaked, and cooked or only cooked without soaking. All these processing techniques lead to changes in the nutritional value of the pulses. Studies have also reported that in addition to nutritional components like Proteins, Carbohydrates, and fats, pulses also contain anti-nutritional components like Lectins, Tannins, and Polyphenols that greatly interfere with digestion of pulses in the human intestine. Hence in the current study a comprehensive review is being compiled to evaluate the nutritional and antinutritional aspects of pulses and effect of processing methods on invitro protein and starch digestibility of the pulses.

1Today, many different methods are applied for the correct use of foods and to prevent their deterioration. Ensuring healthy conditions for people in food consumption and consumption of healthy foods is very important for human welfare. In this study, food spoilage, the factors that cause food spoilage, its effects on a global basis, food transport systems (cold chain) and measures that prevent or delay food spoilage are discussed.

different types of contact, including contact between node pairs, any-contact of nodes, and contacts of the entire network, are used to characterize social relations in mobile social networks. different modes of routing, from the point of view of message delivery semantics, encompass unicasting, multicasting, any-casting, and broadcasting. Studies have shown that using probability distribution functions of contact data, which is mainly assumed to be homogeneous for nodes, improves the performance of these networks. However, there exists an important challenge in studies on distributions. A lot of works apply the distribution of one type of contact to other types. Hence in routing applications, it causes to use of the distribution of one type of contact for any mode of routing. This study provides a complete solution to model each type of homogeneous contact data distribution and to use them in different modes of routing. We propose a routing algorithm that uses this new model. Results show that our solution improves the average latency of comparing methods Epidemic, TCCB, and DR about 3.5-times, 30%, and 45%, respectively. It achieves a delivery rate of about 5% and 6%, and average latency about 6% and 8% better than that of DR and TCCB, respectively.

ABSTRACT Despite a wide range of components and criteria affecting travel behavior presented through empirical research, the results of these studies are inconclusive, which could be due to the difference between these components and criteria in the study areas. Therefore, this research presented a method to determine which factors in different physical developments affect travel behavior due to the differences in various physical developments. The required information was collected through 271 questionnaires at the level of three neighborhoods of Monirieh, Koye Bimeh, and Koye Golestan in Tehran, Iran, as the old, conventional, and new neighborhoods, respectively. ANOVA test was exerted to analyze the significant difference between different development patterns in three neighborhoods. Dunnett's T3 was applied to determine which neighborhood caused the difference between groups. Also, the factors affecting travel behavior were obtained based on exploratory factor analysis indicators. Finally, by comparing the results of the ANOVA test and regression analysis, it was discovered that factors such as car ownership, dependence and pro-liking for private cars, density and access to educational centers and parks, access to medical and service centers, and variety and density of retail stores had been introduced as the factors affecting travel behavior due to the differences in development patterns. However, proximity to the public transportation station, accessibility preferences in choosing a residence, dependence, and pro-liking for other than a private car, having a license, number of children under five years old, and age have influenced travel behavior regardless of the variation between neighborhoods. Extended Abstract Introduction Finding factors affecting travel behavior has been one of the main concerns of transportation planners. However, in the last two decades, the importance of the influence of the features of the built environment, including land use, along with demographic-economic characteristics, travel behavior, and attitudes of people, has been raised by urban planners. Studies seek to find factors affecting travel behavior, especially land use characteristics. Despite presenting a wide range of components and criteria affecting travel behavior, the results of the studies are inconclusive, which could be due to the difference between these components and criteria in the study areas. Therefore, this research presented a method to determine which factors in different physical developments affect travel behavior due to the differences in various physical developments. In order to do this, it must first be determined whether the study areas/different development patterns have a significant difference in terms of travel behavior or not. In case of a positive answer to the previous question, the following question is which study areas caused this difference. The next question arises: -Which physical and non-physical characteristics affect travel behavior due to distinctions between different development patterns?   Methodology The present research method is analytical and experimental based on quantitative methods. This research chose the frequency of travel by private car, public transportation, and walking as the travel behavior. According to the research's purpose, indicators and criteria affecting travel behavior were extracted after reviewing the theoretical and experimental literature. Then, the required information was collected through 271 questionnaires at the level of three neighborhoods of Monirieh, Koye Bimeh, and Koye Golestan as the old, conventional, and new neighborhoods, respectively. The questionnaire was compiled as a Likert scale in five parts of travel information, demographic-economic characteristics, perceptual characteristics of land use, travel habits, and access preferences of people in choosing their residence. ANOVA test was used to analyze the significant difference between different groups of a characteristic (here, different development patterns or the three case studies). Dunnett T3 was exerted to determine which neighborhood caused the difference between groups. Also, the factors affecting travel behavior were obtained based on exploratory factor analysis indicators. Finally, by comparing the results of the ANOVA test and regression analysis, it was discovered which factors affecting travel behavior were due to the differences in study areas and which factors affect travel behavior regardless of development patterns.   Results and discussion This research aims to identify the factors affecting travel behavior due to the differences in development patterns. In this regard, the findings in line with the first research question show that the frequency of three modes of travel, by private car, transportation, and pedestrian, differ significantly in the three neighborhoods. Furthermore, ANOVA test results depict that there is a significant difference between these three neighborhoods in terms of factors affecting travel behavior, such as perceptually environmental characteristics of the neighborhood, dependence and pro-liking for personal cars, variety and density of retail stores, density and access to educational units and parks, access to medical and service centers, and car ownership. Finally, by comparing the results of the ANOVA test with the regression analysis assessing the relationship between physical and non-physical factors (the same indicators in the same study areas) with travel behavior, the factors affecting travel behavior owing to different development patterns were identified. Factors such as car ownership, dependence and pro-liking for private cars, density and access to educational units and parks, access to medical and service centers, and variety and density of retail stores have been introduced as the factors affecting travel behavior due to the differences in development patterns. However, proximity to the public transportation station, accessibility preferences in choosing a place of residence, dependence, and pro-liking for other than a private car, having a certificate, number of children under five years old, and age have influenced on travel behavior regardless of the variation between neighborhoods (different physical development patterns).   Conclusion In In order to discover the factors affecting travel behavior due to the differences in patterns of physical development, this research has provided a more detailed analysis of the factors affecting travel behavior. It has achieved more accurate components than previous studies in this regard. Detailed analysis of studies related to travel behavior and finding the main components affecting it, considering the extent of variables and data, can pave the way for professionals in transportation planning and urban planning, in addition to providing detailed methods and criteria in the related literature.   Funding There is no funding support.   Authors’ Contribution Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.   Conflict of Interest Authors declared no conflict of interest.   Acknowledgments  We are grateful to all the scientific consultants of this paper.

Automatic topic detection seems unavoidable in social media analysis due to big text data which their users generate. Clustering-based methods are one of the most important and up-to-date categories in topic detection. The goal of this research is to have a wide study on this category. Therefore, this paper aims to study the main components of clustering-based-topic-detection, which are embedding methods, distance metrics, and clustering algorithms. Transfer learning and consequently pretrained language models and word embeddings have been considered in recent years. Regarding the importance of embedding methods, the efficiency of five new embedding methods, from earlier to recent ones, are compared in this paper. To conduct our study, two commonly used distance metrics, in addition to five important clustering algorithms in the field of topic detection, are implemented by the authors. As COVID-19 has turned into a hot trending topic on social networks in recent years, a dataset including one-month tweets collected with COVID-19-related hashtags is used for this study. More than 7500 experiments are performed to determine tunable parameters. Then all combinations of embedding methods, distance metrics and clustering algorithms (50 combinations) are evaluated using Silhouette metric. Results show that T5 strongly outperforms other embedding methods, cosine distance is weakly better than other distance metrics, and DBSCAN is superior to other clustering algorithms.

ایدز یک نیروی نامرئی، پراکنده و مخرب است که آشفتگی، اختلال و نقص جامعه را در زندگی خانوادگی و روابط بین شخص به همراه می آورد. شیوع ایدز در جوامع مختلف در حال افزایش است و جوانان به علت نداشتن آگاهی کافی در معرض خطر ابتلا به ایدز قرار دارند. پژوهش حاضر با هدف تعیین و مقایسه میزان تاثیر روش های مختلف آموزشی در مورد بیماری ایدز بر آگاهی و نگرش دانشجویان دختر دانشگاه آزاد اسلامی واحد تبریز انجام گرفت. این مطالعه، نیمه تجربی و از نوع قبل و بعد است. روش نمونه گیری تصادفی طبقه ای بود که 100 نفر از دانشجویان دختر مشغول به تحصیل در رشته های پرستاری و مامائی انتخاب شدند. داده ها با استفاده از پرسشنامه در دو مرحله جمع آوری گردید. برنامه آموزشی به سه روش پرسش و پاسخ، کتابچه آموزشی و روش گروهی اجرا شد. جهت تجزیه و تحلیل داده ها از نرم افزارSPSS  (ورژن 15) و روش های آماری توصیفی و آزمون های تی زوج، تی مستقل، آنالیز واریانس یک طرفه و ضریب همبستگی پیرسون استفاده شد. میزان آگاهی و نگرش دانشجویان بعد از آموزش نسبت به قبل از آن افزایش یافته، بر اساس آزمون تی زوج تفاوت معنادار آماری بین میزان آگاهی و نگرش قبل و بعد از آموزش با روش های مختلف دیده شد(P<0.05) . همچنین میزان تاثیرگذاری سه روش آموزشی بر میزان آگاهی و نگرش دانشجویان در خصوص بیماری ایدز یکسان بود. با توجه به نتایج پژوهش، لزوم اجرای برنامه های آموزشی موثر و منظم جهت ارتقای سطح آگاهی و نگرش دانشجویان در زمینه بیماری ایدز مورد تاکید قرار می گیرد و باید آموزش های لازم در خصوص جنبه های بیماری ایدز در تمامی دانشگاه های کشور به دانشجویان ارائه گردد.

Ants are a major part of the ecosystem as they assist in the decomposition process and improve soil quality. In this study the species richness and biodiversity of these arthropods was assessed in the habitats with varying degrees of human impact in Shiraz, Fars Province, southern Iran. To this end, six habitats including three city parks with the least amount of human destruction (Be’sat, Janat, Babakoohi), two habitats with high amount of manipulation in order to agriculture and urbanization (a field and a destroyed garden) and a natural park without any human manipulation as control, were chosen and sampled bimonthly during 2015 and 2106. A total of 6270 ant workers belonging to 30 species, 12 genera, and three subfamilies were recorded. The most abundant subfamily was Formicinae (16 species) followed by Myrmicinae (12 species), and Dolichoderinae (two species). The biodiversity indices showed a greater diversity in both natural park and urban landscape: Be’sat and Janat parks, with the lowest amount of human effects, respectively as well as Babakoohi and the lowest in the field and destroyed garden. Although a significant difference was observed with the habitats (F= 4.255, P=0.004) and the months (F= 4.327, P=0.002) of sampling, there was not a significant difference between Babakoohi, natural park, Janat and Be’sat parks (P>0.05) nor between field and destroyed garden (P>0.05).