Michael C. Stinson

Attractiveness, easiness and other issues: student evaluations of professors on Ratemyprofessors.com

Felton, Mitchell and Stinson (2004) reported that web-based student evaluations of teaching (SET) demonstrated a student preference for course easiness and instructor sexiness. This study explores these same relationships with a larger and improved database. Results indicate even stronger relationships than previously reported. In addition, this study demonstrates significant cultural differences by institution and discipline in the relationships between quality, easiness, and hotness in web-based SET.

Optimizing the Scalability of Network Intrusion Detection Systems Using Mobile Agents

Modern Intrusion Detection Systems (IDSs) are distributed real-time systems that detect unauthorized use or attacks upon an organizations network and/or hosts. The components of most distributed IDSs are arranged in a hierarchical tree structure, where the sensor nodes pass information to the analyzer nodes. Optimal placement of the analyzer nodes results in an improved response time for the IDS, and isolation of attacks within the IDS network. Since the network topology and workload are constantly changing, we are able to maintain near-optimal placement of the analyzer nodes by instantiating them as mobile agents. The analyzer nodes may then relocate, reproduce or be deleted as necessary. Such flexibility improves the response times and the stability of an IDS. The movement of the analyzer nodes also offers some protection against denial-of-service attacks, since secure analyzer nodes will be relocated to take over some of the functionality of the host under attack.

An Approach to Analyzing the Windows and Linux Security Models

When assessing the potential security risks that exist in the features of different operating systems, there is not a common set of metrics. As a result, it is very difficult to objectively assess the risks associated with a specific feature in the operating system. In this paper, we propose a simple set of metrics to quantify and measure the security risks associated with a specific feature or configuration of any operating systems. We present how the risks in a specific feature in Windows can be quantified and measured with the formula and metrics we have developed in this study. Further more, it is also applicable to other operating systems such as Linux

The impact of machine learning on expert systems

Expert systems are a well-known and well-received technology. It was thought that the performance of a domain expert could not be duplicated by a machine. Expert systems technologies have shown this to be a false belief, and indeed have demonstrated how experts themselves can come to depend on expert systems. Expert systems enjoy widespread use in industrial domains and further uses are planned. The growth in acceptance has been explosive since about 1986. Continued rampant growth appears to depend on cracking the so-called knowledge acquisition bottleneck. The knowledge acquisition bottleneck limits the scalability of expert systems. While it is relatively straightforward to populate a small-scale knowledge base, it becomes more difficult to maintain consistency and validity as the knowledge base grows. Thus, it is important to automate the knowledge acquisition process. A by-product of this process is that any failure of the expert system will be “soft.” The question is, “What impact can machine learning technologies have on knowledge acquisition in the large?” The true test will be on prospective industrial applications in areas such as biology, education, geology, medicine, and scientific discovery. Machine learning technologies include expert systems, genetic algorithms, neural networks, random seeded crystal learning, or any effective combinations. Relevant subtopics include: Second generation expert systems — progress and prognosis Repertory Grids The importance of symbolic and qualitative reasoning The acquisition of fuzzy rules The best learning paradigm or combination of paradigms Impact of machine learning on explanation systems The role of toy domains such as chess Automatic programming revisited Applications to computer vision, decision support systems, diagnosis, helpdesks, optimization, planning, scheduling, et al. Implementation issues using SIMD and MIMD platforms Sources for joint sponsorship Forming industrial partnerships Forming alliances abroad

A Simulation Of Final Stop Consonants In Speech Perception Using The Bicameral Neural Network Model

This paper demonstrates the integration of contextual information in a neural network for speech perception. Neural networks have been unable to integrate such information successfully because they cannot implement conditional rule structures. The Bicameral neural network employs an asynchronous controller which allows conditional rules to choose neurons for update rather than updating them randomly. The Bicameral model is applied to the perception of word-final plosives, an ongoing problem for machine recognition of speech.

Innovation through Visualization

The teaching of programming has numerous theories and directions that can be taken, many of which are debated on their effectiveness. This leads the entire process to be more of an art than a science. This talk sets out to discuss a specific direction taken in the third class in Central Michigan’s track of teaching computer programming which has shown to excite students and give rewarding results for professors. We will explain how the use of simplified visualization tools was added to the foundational knowledge of the students, thus creating an environment that promotes innovation and improvements. The tools allow students to build the graphical user interface of the program in a drag-and-drop environment rather than manually typing out the underlying code. Though the results are preliminary, the improvements have been dramatic in enabling students to utilize their full potential to innovate and create, turning assignments from a checklist to a jumping-off point.

SMS notifications for missed calls expanding mobility for TDM environments

Users expect more mobility options for the services they use, including their corporate extension. For organizations who own PBXs, there can be financial barriers to adoption of services to support extension mobility. There are solutions to provide greater support with little to no cost. This article lists the steps that were taken to send missed call notifications via SMS when a user missed a call on a desk phone. This system infers the users context as out of office when they miss a call, and quickly alerts them with relevant details such as time, calling number, called number, and even attempts the find the calling user. In doing so, the system attempts to provide greater mobility to end users than calling into a remote voicemail system to occasional check for messages, without even knowing if they missed a call to have a message. Index Terms-missed call, SMS, CDR

Study of One Dimensional Molecular Properties Using Python

One of the attractions to the study of one dimensional systems is the technological interest of their possible effects in nanoelectronics [1]. There are myriads or papers on the solution to the problem of the electronic properties of one dimensional systems. Few of these papers use python for visualization but none has used python as a tool for solving this problem from first principle. In this paper, we present several techniques of using Python as a tool in computational analysis. We report the results of using python to study the electronic properties of an infinite linear chain of atoms. We use the principles of nearest neighbor and directly calculated the eigenvalues of our system. We also derived the green function for the system and compared the eigenvalues obtained from the green function with those directly calculated. Visualization of our results was achieved using Matplotlib, a powerful yet, easy to use Python plotting library. Our results show an agreement between the eigenvalues obtained by direct calculation and those obtained using our derived green function for the system. The results also show the simplicity of Python as an analytical tool in computational sciences.

Improving the general monitoring system

Monitoring network devices is critical to avoid downtime in an organization from solvable technical problems. Available methods to monitor hardware are often lacking in areas such as data gathering and visual representation of that data. Gathering accurate measurements at a consistent rate is important for identifying and solving problems. Interpretation of the results is also vital. Visually based data representation has become a standard methodology for many users, as it allows quick analysis of gathered measurements. This paper offers a solution that provides improved device handling as well as an improved visual representation of results from network devices, and increased speed in the data gathering process.

Object-oriented software product metrics (tutorial)

In this tutorial the concept of measuring is discussed ahg with tbe statistical rationale underlying tbe data that need to be collected to calculate meaningful measures of objectoriented software products. A taxonomy for current object-oriented software measures is presented and current measures are classified according to this taxonomy. Current measures are evaluated as to strengths and m~esses. 1.1