A Decision Support System (DSS) is a computer-based information system that assists human decision makers in exercising judgment but does not make the decision itself. DSS helps management by identifying negative trends, allocating business resources more effectively, and presenting information in the form of charts and graphs, i.e. in a summarized format. The telecom industry generates a large volume of data on a daily basis due to its large client base. Decision-makers and business analysts stressed that acquiring new customers is more expensive than retaining existing ones. Business analysts and Customer Relationship Management (CRM) analysts must comprehend the causes of customer churn, as well as the behavioral patterns revealed by data from existing churn customers. Models were applied to a 3333-record telecommunications dataset. The results of the experiments revealed that the Logistic Model Tree (LMT) method and JRip are the best methods for this dataset; with a 96 percent accuracy improved using neural networks from previous research. Multilayer Perceptron is recommended because it has a 94 percent accuracy rate. J48 and PART accuracy was 95%, while naive Bayesian accuracy was 90%. Keywords: Decision Support System (DSS) Customer Relationship Management (CRM); Decision Makers (DM); Telecommunications; Logistic Model Tree (LMT)
The learner's self-esteem: the context leading to modern educational route such as 1) achieving their challenging goals reveals learner's predicaments and worries that their time frame might be consummated but the academic absorption and experience build-up is far from expectations. The findings can be potentially life-changing for learners in reshaping their learning avenues while it is also commendable for an academic institution to find remedial action that in one way or the other, help lighten the burden carried by learners' shoulders as they face the challenging life goals. 2) Values and ideals, suggested that part of the "new normal", the re-education should be established despite the difficulties since it has been noted that to maintain the learner's holistic personality lies largely on in-person activity 3) Goals and standards suggest that crafting, implementing of goals and standards for every institution should be clear. More so, that the learning practice today is shaken by the test of time, building and developing learners' self-esteem lies largely on the degree by which the goal and standard of the institution are implemented. 4) Performance reveals the likelihood that the distance learning of today serves as a link where students/learners' performance are dependent and can be more extensive through in-person learning. 5) Recognition shows that learners are looking forward to availing themselves, enjoying, and experiencing some forms of academic-related activities that are as a culture, being practiced. They are also inclined to have it outside the use of the social media platforms and making it different by which they consider the activity as lifetime experience 6) rewards reveal that they are more likely to receive rewards for the job well done but considering the time where restrictions overruled the societal experience, the loss of confidence and their self-esteem is evident due to the unfavorable turn of events. These are factors that contributed much to student development and hence, building their self-esteem in the presence of these uncertain times could be viewed in a negative position, and hence, strategy is needed to uplift students/learners' learning magnitude despite facing some degree of uncertainties. Generally, the attack of the COVID-19 is the source of all difficulties that make learners' self-esteem mellow down. Now, the institution must invest its capital in non-pharmaceutical facilities to address the declining learner’s self-esteem.
Agriculture plays a vital role in every nation economy every nation. It represents a substantial trading industry for an economically strong country. Remote sensing and Geographic information system used to analyze and visualize agricultural environments has proved to be very beneficial to farming community as well as industry. In this paper I tried to overview the application of remote sensing and geographic information system in agriculture. Reliable and timely information on types of crops grown, their area and expected yield is importance for government for agriculturally based country. The intrinsic characteristics of agriculture make remote sensing an ideal technique for its monitoring and management (Chen et al., 2004). These characteristics include: (a) Agricultural activities are usually carried out in large spatial regions, which makes the conventional ﬁeld survey or census time-consuming and usually costly; (b) the per-unit-area economic output from agriculture is not so signiﬁcant in comparison with other industries; (c) most of the crops are annual herbs having different growth and development stages in different seasons which means that agricultural activities have obvious phenological rhythms and the intra-annual change may be very drastic; (d) agriculture is strongly affected by human activities and management where timely and accurate monitoring information is required.. Remote sensing technology has been applied in agriculture extensively since its early stage in the 1960s. Now several global and national operational systems of monitoring agriculture with remote sensing have been operated. The number of similar operational systems at regional scale is much more. These systems provide timely and valuable information for agricultural production, management and policy-making. On the other hand, the demands arising from the applications in agricultural sectors have also enhanced the progress and innovation in remote sensing technology.
Abstract Sign language recognition is one of the most rapidly increasing disciplines of study today, and it is the most natural mode of communication for those who are deaf or hard of hearing. A gesture recognition system can allow persons with hearing impairments to interact with others without the need for a translator or an intermediary. With a tailored dataset, the system is set up for automatic recognition of American Sign Language. It can be taught to recognize any sign language in the world for which there is no well-established dataset. The suggested system allows any user to learn sign language using human sign language characters and a word database, and the training is provided offline. In the suggested approach a bigger sample is considered to identify the words that are taken using a camera and are not part of the regular sign language. In order to improve overall performance, picture pre-processing phases are employed to modify the image. For this first median and Gaussian filters are used to minimize sounds and morphological techniques are used as the pre-processing stage. Then Hue Saturation Value (HSV) color space is used to distinguish the palm from the arm. After that, for histogram equalization hands are set using the 5 x 10 boxes which can be kept for model training as well as recognition. TensorFlow object detection api used to build a model for a specific object identification which makes the entire methodology more approachable. Convolutional Neural Network (CNNs) can automate the process of feature building rather than constructing intricate handmade features. We have a good level of accuracy in recognizing 46 gestures. Keywords – Motion modeling, TensorFlow, convolutional neural network, deep learning, gesture recognition, sign language recognition