Chandigarh University

About: Chandigarh University is a education organization based out in Mohali, India. It is known for research contribution in the topics: Materials science & Computer science. The organization has 1358 authors who have published 2104 publications receiving 10050 citations.

9E model and e-learning methodologies for the optimisation of teaching and learning

Abstract: Education is an important field in today's world without which it is impossible to outlive in the society. Education has been evolving since ancient times and has been overhauled in many ways with the advancements in technology. Today education technology is playing a significant role in bringing up the levels of teaching and learning with the use of enormous educational tools and strategies. In this paper we will be scrutinizing the process of education and introducing a new model that is the 9E teaching and learning model which is an enhancement to the previous 7E model. This paper also sheds a light on the various methods and strategies opted for intensifying the process of teaching and learning in order to optimize the whole education system.

Significance of Diatoms in Diagnosis of DrowningDeaths: A Review

Abstract: Diatom test is an important tool in diagnosis death in drowning cases. As the typical features of ante-mortem drowning disappeared very rapidly with commencement of putrefaction and hence diatom test plays an important role for diagnosis and confirmation of drowning deaths. Diatoms have number of characteristic like their widespread presence in water, high diversity in species, habitat specificity and have a good potential for preservation and thus this group can be used in forensic geosciences for criminal investigations. Extraction and identification of diatoms present in the tissue samples can be used as supportive evidence in drowning and also for site specific diatoms. Temperature and pH variations also play important role in the distribution of diatoms in a particular location. Diatoms species detection in both water and tissue samples gave a reliability of the diatom test in solving cases pertaining to drowning deaths. Hence the possible means and methods must be practiced on a regular basis by the forensic examiner as well practitioners so that new possibilities must always be explored for extraction and identification of diatoms in near future. This paper reviews the recent year’s progress on diatom test and its application in forensic science.

Performance analysis of basin-type vertical multiple-effect diffusion solar still integrated with solar pond: energy, exergy and economical analysis

Abstract: An experimental analysis was carried out with basin-type vertical multiple-effect diffusion solar still coupled with solar pond (BVMEDS-SP) to evaluate 24 hours overall performance of still by varying feed flow rate and temperature in addition to other affecting parameters. A solar pond was utilized to harness solar energy diurnal and the same energy was provided to basin water nocturnal in batch mode to produce distillate throughout the day. It can be seen that the daily energy and exergy performance of BVMEDS-SP having four effects was improved by 21.74% and 16.83%, respectively, when the feed flow rate was reduced from 0.32 g/m2/s to 0.13 g/m2/s. As the temperature of feed water was enhanced from 25.65°C to 32.4°C, the daily energy and exergy efficiency of BVMEDS-SP correspondingly increased by 41.76% and 46.62%. In addition, increasing the number of effects from 2 to 5 improved the overall energy and exergy efficiency to 93.15% and 171.80%, respectively. The cost analysis revealed that cost of distillate for 2-effect still was Rs. 4.64/kg and it reduced to Rs. 3.11/kg for 7-effect still. A productivity correlation was furthermore developed and estimated that the experimental database of current research was in good agreement with the error band of −5% to +10%.

A dual deep neural network with phrase structure and attention mechanism for sentiment analysis

Abstract: Sentiment analysis of short texts is difficult for their simplicity and compactness. This goes a step further when it comes to the Chinese texts. Although deep learning achieved better accuracy in sentiment analysis, there is a lack of explain-ability. Thus, this paper evaluates the effectiveness of techniques for sentiment analysis of Chinese short financial texts with deep learning. For this, we built a Chinese short financial texts corpus (CSFC) and designed an ablation experiment. Beside the CFSC, we used a Chinese review collection and an English short-text repository in the experiment for comparison. There are five techniques involved. They are the Pinyin, the segmentation, the lexical analysis, the phrase structure and the attention mechanism. As results, we found that the phrase structure and the attention mechanism are two of the best. Therefore, the best model in the experiment is called a Phrase Structure and Attention-based Deep network model (PhraSAD). Moreover, to improve the classification accuracy on neutral data, we use a dual classifier strategy for 3-class problems. Experimental results showed that PhraSAD outperformed all other compared models on all experimental datasets.