how to handle Food Waste mobile app information - Codeshoppy

 how to handle Food Waste mobile app information - Codeshoppy

Wasting food is a common problem in our society. Food waste management is crucial since it can improve our environmental and economic sustainability. We have identified the use of mobile technology to reduce food waste management and built an android mobile application that allows restaurants to donate and share their foods and leftovers with people in need. This app will enable users to register, login, view items, add items, add items to cart, remove an item from the cart, and log out. This app is using the firebase storage and real-time database. Any user in need can see all the food images donated by different users and add it to his or her cart.  read more

 

Mobile phone applications have seen wide use in recent years . It's known that Android is the most popular
platform for mobile, right now android is used on over 190 countries in the world on millions of mobile devices. Androidis the most installed platform for mobile, and the number isincreasing rapidly since almost 1 million users every daypurchase new Android devices and use it immediately to getdigital content such as games, application, and many other services . Due to that, we developed an android application “FoodReduction App” using android studio because it will reach a wider range of audience since most people nowadays use android phones. To improve the performance of the image processing algorithms, noise estimation can be used to adapt the detection step. buy online app

 

 

The purpose of this development is to limit the wastage of food in the United Arab Emirates. Many restaurants tend to throw the leftover food at the end of the day even though the food is perfectly fine to be eaten, which means that huge amounts of food are wasted. While all that food is being wasted, some families can barely afford proper meals with their limited money. They don't get enough nutrition due to the lack of having threemeals in a day. Therefore, we decided to createour application to link the restaurant with the unfortunate know more
people, so instead of throwing the food, the unfortunate will beable to pick it up from the restaurant at the end of the day. Theapplication allows the restaurants to log in, and upload animage of the meals they have as leftovers along with adescription of that meal, and the location where to pick it up.The users then, can log in and choose the meal suitable to their choice and can pick it up once they send a request to the application. 

 

In the production of food many resources are required. A country’s food requirement in equivalent resources unit can be roughly converted to 10 percent of the total energy budget, 50 percent of land used, and 80 percent of freshwater consumption. In addition to these fertilizers and pesticides are also used. And on the global front the same can be converted to 70% of planet’s fresh water withdrawals, 80% of the world’s tropical and subtropical deforestation and 30 to 35% of human caused greenhouse gas emissions  

 

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Research on The Framework of Library Management - Codeshoppy

 Research on The Framework of Library Management - Codeshoppy

view of the traditional library management method, with low efficiency and single operation mode, this paper designs the information infrastructure and key mechanism of library management system, and discusses the innovation of system service mode from the aspects of readers' information acquisition and modification, fast management and delivery of books. With RFID technology as the core, through the comprehensive design of relevant subsystems, the key problems related to library management are solved, and the intelligent application scheme and overall architecture based on RFID are proposed. Finally, while realizing the basic functions, the RFID system of public library will be established into SAAS and cloud computing platform, and a set of integrated library information management system based on IoTs is designed. Library Management System

The Digital Library for Earth System Education (DLESE) is a distributed community effort that involves educators, students, and scientists working together to improve the quality of Earth system education. A core philo sophy is users-as-contributors. Members of the DLESE community contribute educational resources and collections, devel op services that enhance its usefulness, participate in library governance and planning, andcontribute ideas and feedback on how to improve the library. GetNow

 

There is a strong need for tools and systems that enable thevarious groups to manage internal and external collaboration and communication, as well as develop their own websites usingDLESE templates. This poster w ill showcase several tools that DLESE has developed to address these needs. Included arecustomized versions of swiki and plone (open source contentmanagement systems), into whic h we have integrated our Webservices. These include DLESE Search (a customized version ofthe DLESE search system that lets users control the parts of the library over which searching is performed), smart links(predefined queries), and RSS f eeds. The poster will provide anoverview of the tools and address i ssues related to their effective use.more details

Managing library manually, i.e. based on pencil and paper, was common practice in many libraries including school libraries. Based on the empirical observation at two private schools in Surakarta City, Indonesia, it can be noted that problems usually arise in manual process in library are including (1) the time spent for borrowing, extension and returning transaction, (2) the difficulty of tracking the books and other loanable resources, (3) the time spent for compiling report, (4) the time spent for checking whether the student has returned the book, and (5) although not significant, the security of the book from the thief. Another key requirement is the implementation cost should be low.  

 

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Online Shopping for Android, PHP, Dotnet & Django Python Projects - CodeShoppy

 Online Shopping for Android, PHP, Dotnet & Django Python Projects - CodeShoppy

Web is a specific interactive system which is in a wide range of application areas, but there are with different degrees of usability problems. Therefore, it is necessary to provide a design method for Web usability. Based on the theory of user centered design (UCD) and usability engineering principles, Web usability design includes three aspects: user research, Web design, and Web evaluation. User research focuses on target users, and researches user's goal, behavior and views by user modeling based on personas. Web design focuses on information architecture design, readability design, search design and page design to design the self-described Web user interface with high-usability. Web evaluation is a measuring means for iterative process of Web usability design. The method will be a guideline to design and improve Web usability for designers.

Web is hailed as one of the greatest inventions in the twentieth century, and its rapid development not only provides unprecedented convenience channels for global communications, but also affects all aspects of human life. Most websites are ever growing, evolving collections of information and services.These information and services have been a large number of applications in the office, business management, shopping, and entertainment etc. They provide much wider opportunities for businesses and much richer services for users. At the same time, Web is a complex information environment, and a specific human-machine interactive interface. Compared to the traditional software interface, Web interface is back at least 10 years . 

 

 

 

As using Web, users find it difficult to learn, complex to operate, or not easy to understand. According to Jakob Nielsenÿs studies, websites are with different degrees of website usability problems generally. If the user isn’t satisfied with it at the first visiting, 40% of users will not visit the site again. Thus, the usability problems of websites have broad universality and severity, and will have a negative impact on websites’ development. Therefore, in Web time, to achieve the purpose of the site, it should allow users to feel good usability. Web usability has moved from a “nice to have” to a “must have” . We must find ways to reduce usability problems, and design high-usability website.

 

The only goal of the human-computer interaction (HCI) is to meet user needs and expectations as much as possible, and then to improve the usability of software systems. Usability methods have from the beginning of times, that is to say the early 80’s, always included users to varying degrees. The usability is an important indicator of quality of the interactive IT product or system. Nielsen has pointed out that the usability is effective, easy to learn, efficient, easy to remember, the fewer mistakes and satisfaction for product users . The international standard ISO 9241-11 defines usability as follows: effectiveness, efficiency and satisfaction what are qualities of products in a particular environment for a specific user for specific purposes. The concept of usability engineering appeared, as people have an emphasis on the quality of product since the 80s of last century, and then has correspondingly formed a popular area in academia and industry. Usability engineering is an engineering methodology for the IT product and user interface development, throughout the product life cycle stages. Its core is UCD methodology, stressing from the user's point of view to design and development . 

 

 

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The Study on Estimate of College Information Management System

College Management System Project

The Study on Estimate of College Information Management System

Multiple Subjects of College Information Management System Estimate In each of the categories there are very specific mechanisms which must exist in a model of information system architecture. Measuring scales are developed in order to record whether or not the model meets the criteria in each category. For some conditions a natural scale exists and is used as a measurement. In all other areas a binary scale is used. In the case of the binary scale, a zero indicates that the model does not meet that condition, and a one indicates that the condition is met.

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Project Team of Information SystemProject team of information system develop, implement and control the system, of which the project manager is the head, and system analysts, programmers, persons participating in the system development and implementation are the members. Therefore, what the project team are mainly concerned about are the technology of the information system and whether the system functions according to the schedule, budget and goals set. The estimate indexes mainly include: 1) Index for evaluating system construction: It mainly evaluates the implementation and management of the information system, such as the satisfaction degree of users, development efficiency of the system, the utilization rate of resources, normalization degree of system construction and whether the overall system is advanced, etc; 2) Index for evaluating system performance: It mainly evaluates the reliability, efficiency, adaptability, maintainability, transportability, expandability, and safety and confidentiality of the system.
College ManagementStaffs College management staffs are usually the initiator and advocator of information systems, who initiate, plan, organize, coordinate and support the implementation of information systems, and whose support is the key to the successful implementation of information systems. College management staffs are concerned about the overall interest and long-term development of the college. They support the implementation of the information system to realize the strategic goals and sharpen the competitive edge of the college, such as improving the college image and attracting more clients. Therefore, College management staffs, when evaluating the system, would take the tangible and intangible interests the information system brings into consideration, which mainly include: 1) Operation interest: Saving cost, shortening time of turnover, enhancing productivity, improving service quality, etc. 2) Management interest: Optimizing resource management, etc. 3) Strategic interest: Supporting innovative expansion of business and e-commerce, etc.; therefore, system progress, whether the system supports cooperation with external parties, and global expansion of business and e-commerce, etc are the indexes for estimate. 4) Fundamental interest of IT: Improving the flexibility of business, saving IT cost, enhancing basic capacity of IT, etc. 5) Organization interest: supporting the reformation of the organization, promoting training and improving skills of staff, and setting up common goals, etc.
External Entities The implementation of college information system will affect the partnership with clients and suppliers, etc. Therefore, external entities like clients and suppliers would also evaluate the implementation of the information system. Besides, the external entities also include the estimate agency and consulting agency, etc. [2] Things that external entities like clients and suppliers concern about fall into 4 categories: time, quality, performance, service and cost. Therefore, they are mainly concerned about how the information system can bring them value and satisfaction from the four aspects mentioned above. The estimate indexes include: 1) Whether the implementation of the system shortens the response time, 2) Whether the implementation of the system improves product and service quality, 3) Whether the implementation of the system brings larger value, 4) Whether the implementation of the system reduces product or service cost. Learn More

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Analysis on Complaint Behavior of Electric Power Customers

Online Road Complaints Registration System

Analysis on Complaint Behavior of Electric Power Customers

The data of electric power customer complaints from EZ power supply company in Hubei Province from January 2015 to May 2018 is obtained. During this time period, EZ power supply company received a total of 622 complaints from 95598 hotline. The annual distribution of complaints is shown in Table I. The highest number of complaints was in 2016, a total of 238, which fell sharply in 2017, but rebounded in 2018. There were 75 complaints from January to May 2018, with an increase of 62 cases compared with the number of complaints in the same period in 2017. The complaints were mainly concentrated in the rural network, a total of 507 cases, accounting for 81.51%. There were 115 cases in the urban network, accounting for 18.49%. Code Shoppy

According to “The handling regulation of power supply service complaints” from SGCC, electric power customer complaints can be divided into five types, including power supply quality complaints, business complaints, service complaints, power grid construction complaints and power outage and supply complaints. Power supply quality complaints refer to the complaints caused by long-term power supply quality problems, which affects customer normal life and production, such as voltage deviation, frequency deviation, voltage imbalance and voltage fluctuation or flicker. Business complaints refer to the complaints caused by working timeout, negligence and error happened in the process of handling the specific business operation. Service complaints mean the complaints caused by irregular service behavior of power supply company employees, inadequate and inconvenient service channels of power supply company. Power grid construction complaints imply the complaints happened during the process of power grid construction, such as incomplete transformation of power supply facilities and irregular power construction. Power outage and supply complaints refer to the complaints caused by service errors in the process of power outage, supply management and on-site emergency repair services. Table II shows the classification and proportion of 622 complaints from EZ power supply company. Among these 622 complaints, the number of power supply quality complaints was the maximum, 241 cases, accounting for 38.75%; followed by 151 business complaints, accounting for 24.28%.
The number and proportion of customer complaints from 2015 to 2018 are shown in Fig. 1. The proportion of power supply quality complaints and power grid construction complaints increased at first and then decreased, which indicated that the effect of power network reform in the past three years was remarkable. The proportion of business complaints and power outage and supply complaints decreased at first and then increased.
There are 24 power supply stations in this regional power grid. Each power supply station is responsible for one town. The population of each town is different. Fig. 9 shows the total number of complaints and the number of complaints per 10,000 households in each power supply station. HH power supply station has the largest number of complaints among these 24 power supply stations, with a total of 64 complaints. The biggest amount of complaints per 10,000 households is YY power supply station, with 28.43 cases per 10,000 households.
From 2015 to 2017, complaints from seven power supply stations, such as HH power supply station, have declined year by year. There is no complaint from CG and JK power supply stations since 2017, and no complaint from DS power supply station since 2016. However, complaints from TH power supply station increase year by year. From January to May 2018, the total number of complaints from 19 power supply stations increase year-on-year. The complaints from GK power supply station have the maximum increase, with an increase of nine. There are 20 power supply stations whose power supply quality complaints have the largest proportion of the total number of their complaints. Fig. 10 shows the distribution of power supply quality complaints in power supply stations. GK power supply station has the largest number of complaints about power supply quality, with 32 cases. Four power supply stations have no power supply quality complaint for three consecutive years. The number of power supply quality complaints per 10,000 households in YY power supply station is the maximum, 16.72 cases per 10,000 households.
Fig. 11 shows the distribution of business complaints from power supply stations. HH power supply station has the largest number of business complaints, with 21 cases. Three power supply stations have no business complaint for three consecutive years. The number of business complaints per 10,000 households in YY power supply station is the maximum, 8.36 cases per 10,000 households.
Fig. 12 shows the distribution of service complaints from power supply stations. HH power supply station has the largest number of service complaints, with 10 cases. Four power supply stations have no service complaint for three consecutive years. The number of service complaints per 10,000 households in DD power supply station is the maximum, 4.01 cases per 10,000 households.
Fig. 13 shows the distribution of power grid construction complaints from power supply stations. TZH and ZS power supply stations have the largest number of power grid construction complaints, with 6 cases. Three power supply stations have no service complaint for three consecutive years. The number of power grid construction complaints per 10,000 households in TZ power supply station is the maximum, 5.63 cases per 10,000 households.
Fig. 14 shows the distribution of power outage and supply complaints from power supply stations. GD and HH power supply stations have the largest number of power outage and supply construction complaints, with 8 cases. Eight power supply stations have no power outage and supply complaint for three consecutive years. The number of power outage and supply complaints per 10,000 households in TH power supply station is the maximum, 3.27 cases per 10,000 households. Click Here

Group Signature Entanglement in E-voting System

Online Voting System Project Application

Group Signature Entanglement in E-voting System

Xuet al. [4] proposed a scheme which supports anonymity of the voters in the e-voting system by applying the concept of blinding and grouping signature. This scheme seems to be easier than the other quantum signature schemes because i t d o e s not involve entanglement. In t h e e-voting system, the message has to be signed by the manager of the office. However, the content of the message d o e s not h a v e to be readable by any person other than the owner of the message (blind signature scheme). Also, Xu’s paper uses the grouping signature to provide anonymity of voters in the e-voting system, whereas the voter information, such as location information, has to be secure and non-readable by any person. Some e-voting systems could be applied in different branches and offices in different locations, so signing the message from a specific manager might reveal the location information of the voter. Thus, by applying grouping signature with different managers on the same message, f tracing the sender could be eliminated. However, the verifier cannot know the identity of the signer; he/she can only verify the validity of the signature. This paper is different than some other schemes that propose different services. Xuet al. [4] proposes a blind signature scheme using a group signature scheme for a distributed e-voting system without using the entangled state concept, and this scheme can represent a high level of efficiency. The authors explained some disadvantages, such as using a symmetric scheme. Also, the inspector in this scheme is the only person who can verify the message which makes the scheme elastic with only e-voting systems. In [10], the authors proposed a new quantum protocol that provides anonymous voting with anonymity check. This protocol has two main characteristics. First, the value of a voter’s vote is unknown to other voters and the tallyman. Second, a non-exaggeration t e c h n i q u e h a s b e e n i m p l e m e n t e d to prevent malicious voters from voting twice. Each voter makes a binary decision (0,1); 0 means no and 1 means yes. There is a tallyman who collects the ballots and announces the results. The main idea, after the voting process, is that the ballots arereturned to voters again to allow for two voters to check the anonymity of the vote counting process bypreparing an entangled state of two ballots. Thus, any attempt by a curious tallyman to g a i n information about voting results leads to th e d e st r uc tio n of the entanglement, which can be detected by the voters. The entangled state is generated using one of four Bell bases to create a Bell state as follows: The four Bell bases are:√√√√The voters carry out the ballot test: – The voters who have chosen to vote measure their qubits in computational basis. If there is a difference from the sent ballot, they state the ballot test failure. – On the other hand, the voters who have chosen to check the anonymity make the measurement of their qubits in the Bell basis. If there is a difference from the Bell state, they state the ballot test failure. Suppose a curious tallyman makes an additional measurement of qubits to gain information about voters. For example, to learn the vote of voter i, the easiest way is by measuring the ith qubit in computational basis. If voter i has chosen to vote, this attack will be unnoticed. But if voter i has chosen to check the anonymity with voter j, this leads their state to be transformed into (0,1) or (1,0) with equal probability of 0.5, which means anonymity check test failure. Therefore, the curious tallyman will be detected. Xiaoqiang proposed in [11] a blind signature scheme that is based on quantum computing. The scheme combines proxy and blind signatures. The scheme consists of four parties. They are Bob, who is the message signer; Charlie, who is the message owner; Alice, who prepares the proxy warrant message; and Trent, who is responsible for delivering the two particles to Bob and Charlie and verifying the signature.

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The authors used BB84 quantum protocol for key distribution. They applied quantum entanglement for the signature generation and verification process. Using a one-time pad encryption algorithm provides unconditional security and prevents eavesdropping. In [12], the authors propose a blind quantum scheme based on a two-particle entangled system. It combines proxy and blind signatures and consists of three parties. Alice is the message owner, Bob is the message signer, and Charlie is the message arbitrator and Bob’s proxy. This scheme can be used in privacy-related protocols. The authors used entanglement to the blind signature generation process and the verification process. The key distribution method is not explained in this paper.
We proposed a new scheme that enhanced an existing one that solves the check back e-voting anonymity to solve the problem of denying the value of the ballot. By implementing the concept of the entanglement between two random voters, the signer candetermine the correct value of the ballot. However, this scheme has a simple weakness which shows up when the signer (Bob) tries to contact the second voter (Nancy) asking her for the qubit, but she does not respond. We are planning to extend this scheme to address this problem by keeping the original qubits in a separate database somewhere in the system. Code Shoppy

Detection of Anomalous Behavior In An Examination Hall Towards Automated Proctoring

Exam Hall Ticket Management System

Detection of Anomalous Behavior In An Examination Hall Towards Automated Proctoring

The paper proposes a workflow for the automaticdetection of anomalous behavior in an examination hall, towards the automated proctoring of tests in classes. Certain assumptions about normal behavior in the context of proctoring exams are made. Anomalies are behavior patterns that are relatively (and significantly) different. While not every anomalous behavior may be cause for suspicion, the system is designed to detection typical patterns for actions of concern such as discussions during an exam or the turning around or the passing of notes, etc.

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This detection is based on features computed using the histogram of gradient orientations followed by a nearest -neighbor search through annotated patterns of pre- recorded clips to train the system for behavior that may cause concern. While there may be false positives, the system is intended as a decision support system to facilitate automatic proctoring of tests and deters malpractice.

In recent years, with the rapid development of computer technology, video surveillance technology has made considerable progress in many areas. But the traditional method of video surveillance is fulfilled by personnel monitoring, which is a heavy workload.Video Analytics is a technology that is used to analyze video for specific data, behavior, objects or attitude. This paper studies the automatic surveillance methodology in Examination hall, which can detect abnormal behavior in real time. It assumes that for any specific context, there is a notion of what constitutes normal behavior and conversely abnormal behavior. Anomalies stand out to be as different relative to the context of their surrounding in space of time. Hence it is a good way to solve this problem using this technology [1].
Video surveillance can be an effective tool for today’s businesses both large and small such as in video surveillance inexamination halls, security surveillance and deterring dishonest and deceitful behaviors [2].For such systems it is needed to design a core which uses a method to detect human actions, classify them based upon several actions in sequence.However, building an abnormal behavior recognition system is a challenging problem because of the variations in the quality of the video, environment size and certain postures of the humans. Environment of the examination room is crowded and dynamic, which imposes challenge for current approaches to video action detection because it is difficult to segment the student from the background due to disrupting motion from other objects and the scene. All of these make it difficult to satisfy the application in the real-world scene [5].Some of the main applications of Human Behavior detection are crime detection in sparsely populated areas like ATMs, automated sports commentary, intrusion detection, and detection of jaywalking on roads, characterization of human gait, person counting in a crowd, gender classification and fall detection for elderly people. In today’s world with increase in technology, systems can be developed and used to detect human activity. This paper aims at detecting human activities which are then classified into different categories. These categories are then studied, identified and interpreted as normal or abnormal behavior. The aim focuses on developing this system to urge an increase in the security system and services provided for the security of examination authority.The paper proposes a system for abnormal activity detection in examination hall videos using K Nearest Neighbour (KNN) which encode scene rules and are used to smooth sequences of actions. High-level behavior recognition is achieved by computing the probability that a set of predefined KNN’s explains the present action sequence.
This system is deployed in an examination hall where the student’s activities and behavior are monitored on a surveillance camera. System accepts video as the input and an automatic alerting system alerts the relevant authorities when required. Based on the predefined anomalies, the activities are categorized as normal or abnormal behavior.
This paper deals with designing an approach wherein it tries to detect any abnormal behaviors present in the videos. The system first works by detecting all students present in the video. After detecting all the students, it tracks the detected students throughout the course of the video. The features of the tracked students are calculated using HoG feature descriptor and then sent to the K-Nearest Neighbor classifier. The classifier is pre-trained to detect normal or abnormal actions. System is made to be adaptable to lots of different conditions as in, a user can choose the behaviors that they want the system to detect and train the system specifically for that. This means that it can be used across a variety of situations and conditions from normal surveillance to security related monitoring. This system is also capable of detecting abnormalities if there are more than five people in an exam hall. Learn More
In the area of machine learning confusion allows visualization of the performance of an algorithm. TABLE II indicatesConfusion matrix of the system. Each column of the matrix represents the instances in an expected class while each row represents the instance of the actual class. Confusion matrix reports the number of false positives, false negatives, true positives and true negatives. This allows more exhaustive analysis than mere percentage of correct guesses. All the diagonal values indicate the accuracy of each action detected.