240 research outputs found
Ananlysis of productivity and efficiency in MSRTC
Maharashtra State Road Transport Corporation (MSRTC) has been instrumental in providing access and connectivity across the entire state of Maharashtra. Over the last few years, due to a variety of factors, particularly competition from the private sector, MSRTC’s financial performance has shown a marked deterioration. After the financial turnaround of Karnataka State Road Corporation when it was split in to four smaller organizations, the same solution was suggested by many for large corporations like MSRTC. In this paper, we examine the issue of splitting MSRTC into smaller regions to find out whether it would actually help in its financial recovery. Also, we examine the possibility of improvement in financial profitability by means of enhanced input productivity.State Road Transport Corporations, Scale Economies, Technical Efficiency, Total Factor Productivity
Management System for a Restaurant
The Management System for a Restaurant is a web-based application. The main aim is to provide better communication between customers and restaurants. By using this application, the user can order from any location. This application will reduce all the manual processes. So, users can view the restaurant menu from nearby locations, and can place an order and view the status of the order like cooking/packed/delivered. There are three main actors in this application: Admin, Restaurant manager and User. The admin will create all menus with their corresponding price lists. Also, the admin will be able to view statistical reports for foods. Restaurant managers will receive orders from customers. Users/Customers can place orders using this application and they will be able to view available food items. The system is designed as a 3-tier architecture. Each user must register with the system; after logging in successfully, they are able to perform operations. Separate login pages are provided for logging into the system. To develop this system, we use HTML, CSS, JavaScript, and bootstrap for the front end, MySQL database as the back end, and Java, JSP, and JDBC as middleware
A method for generating UTS assignments with an iterative state transition algorithm
There is a lack of systematic procedures that can be used to find uni-code totally sequential (UTS) assignments from a flow table description of an asynchronous sequential circuit. Presented here is an iterative internal state assignment method. This method consists of three algorithms. The first generates a minimum variable initial assignment from a flow table description. The second tests the validity of this assignment by constructing minimum length transition paths without crossover and the third augments this assignment by adding an internal state variable in the event that all transition paths cannot be constructed without crossover. The second and the third algorithms are used iteratively until a valid non-universal UTS assignment is produced.
The iterative state assignment method is systematic in all its phases. Every phase of the method includes more than one algorithm to perform the same function. The algorithm producing minimum length transition paths is very powerful in that it can also be used in conjunction with other state assignment methods producing either universal or non-universal UTS assignments.
After one obtains a valid UTS assignment an algorithm is provided to replace some or all of the totally sequential transitions with mixed mode transitions. This reduces the number of subtransitions in a given transition path and therefore speeds up the transition time considerably --Abstract, page ii
PMLC- Predictions of Mobility and Transmission in a Lane-Based Cluster VANET Validated on Machine Learning
VANET refers to a massive network system, to communicate with each vehicle or infrastructure a precision protocol, an advanced view and routing system is required. This means of communication should be appropriate for all kind of vehicles. In this proposed PMLC protocol, which was built on cluster routing in a lane-based road environment. The network requires optimal solutions to form the cluster and choose its leader. All road environment characteristics are chosen, and multilayer estimations are generated to obtain specific deviations and variations, which are calculated based on data transfer and vehicle movement, and exact values are found using the machine learning system. The neural network processes the inputs, selects the required leader, and sends the data to the destination. At the end of this explanation, the execution of this protocol is depicted graphically
Finding Patterns in Biological Parameters
Changes or variation occur in physiological parameters of the body when a person is going through a tough time or he is extremely happy. These changes in physiological parameters can be used for detecting emotions. Emotional computing is a field of Human Computer Interaction(HCI) where we detect human emotions. Emotion recognition based on affective physiological changes is a pattern recognition problem, and selecting specific physiological signals is necessary and helpful to recognize the emotions. In this paper, we have discussed various research papers analysing that how emotions are detected from physiological signals using non-invasive methods. Developers use various Data Mining techniques for developing such results. Heart Rate Variability(HRV), Skin Temperature(ST), Blood Volume Pulse(BVP) are the main highlights as these are key parameters in Physiological signals
Evaluation of Intravascular Ultrasound Catheter Based Transducers using the Resolution Integral
The effects of DAT1 genotype on fMRI activation in an emotional go/no-go task
Dopaminergic brain circuits participate in emotional processing and impulsivity. The dopamine transporter (DAT) modulates dopamine reuptake. A variable number tandem repeat (VNTR) in the dopamine transporter gene (DAT1) affects DAT expression. The influence of DAT1 genotype on neural activation during emotional processing and impulse inhibition has not been examined. Forty-two healthy subjects were classified as 9DAT (n = 17) or 10DAT (n = 25) based on DAT1 genotype (9DAT = 9R/9R and 9R/10R; 10DAT = 10R/10R). Subjects underwent fMRI during non-emotional and emotional go/no-go tasks. Subjects were instructed to inhibit responses to letters, happy faces, or sad faces in separate blocks. Accuracy and reaction time did not differ between groups. Within group results showed activation in regions previously implicated in emotional processing and response inhibition. Between groups results showed increased activation in 9DAT individuals during inhibition. During letter inhibition, 9DAT individuals exhibited greater activation in right inferior parietal regions. During sad inhibition, 9DAT Individuals exhibited greater activation in frontal, posterior cingulate, precuneus, right cerebellar, left paracentral, and right occipital brain regions. The interaction between DAT genotype and response type in sad versus letter stimuli showed increased activation in 9DAT individuals during sad no-go responses in the anterior cingulate cortex, extending into frontal-orbital regions. 9DAT individuals have greater activation than 10DAT individuals during neutral and sad inhibition, showing that genotypic variation influencing basal dopamine levels can alter the neural basis of emotional processing and response inhibition. This may indicate that 9R carriers exert more effort to overcome increased basal dopamine activation when inhibiting responses in emotional contexts
Virtual reality driving simulator for analysis of user response time
Master of ScienceDepartment of Computer ScienceWilliam H. HsuThe purpose of this master’s thesis is to investigate and analyze the ability of individual users of a virtual reality (VR) driving simulator to react to a set of complex scenarios involving various accident-prone scenarios in a mixed virtual environment. The virtual environment is realistic enough to examine the response times in complex scenarios, and to identify the response time taken and the factors affecting it. The final result identifies the response time and represented the correlation between demographics and the driver’s behavior
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