Reviewerly/exHarmony huggingface dataset:
FemtoDet: An Object Detection Baseline for Energy Versus Performance Tradeoffs

Efficient detectors for edge devices are often optimized for parameters or speed count metrics, which remain in weak correlation with the energy of detectors. However, some vision applications of convolutional neural networks, such as always-on surveillance cameras, are critical for energy constraints. This paper aims to serve as a baseline by designing detectors to reach tradeoffs between energy and performance from two perspectives: 1) We extensively analyze various CNNs to identify low-energy architectures, including selecting activation functions, convolutions operators, and feature fusion structures on necks. These underappreciated details in past work seriously affect the energy consumption of detectors; 2) To break through the dilemmatic energy-performance problem, we propose a balanced detector driven by energy using discovered low-energy components named FemtoDet. In addition to the novel construction, we improve FemtoDet by considering convolutions and training strategy optimizations. Specifically, we develop a new instance boundary enhancement (IBE) module for convolution optimization to overcome the contradiction between the limited capacity of CNNs and detection tasks in diverse spatial representations, and propose a recursive warm-restart (RecWR) for optimizing training strategy to escape the sub-optimization of light-weight detectors by considering the data shift produced in popular augmentations. As a result, FemtoDet with only 68.77k parameters achieves a competitive score of 46.3 AP50 on PASCAL VOC and 1.11 W & 64.47 FPS on Qualcomm Snapdragon 865 CPU platforms. Extensive experiments on COCO and TJUDHD datasets indicate that the proposed method achieves competitive results in diverse scenes.
STEERER: Resolving Scale Variations for Counting and Localization via Selective Inheritance Learning

Scale variation is a deep-rooted problem in object counting, which has not been effectively addressed by existing scale-aware algorithms. An important factor is that they typically involve cooperative learning across multi-resolutions, which could be suboptimal for learning the most discriminative features from each scale. In this paper, we propose a novel method termed STEERER (SelecTivE inhERitance lEaRning) that addresses the issue of scale variations in object counting. STEERER selects the most suitable scale for patch objects to boost feature extraction and only inherits discriminative features from lower to higher resolution progressively. The main insights of STEERER are a dedicated Feature Selection and Inheritance Adaptor (FSIA), which selectively forwards scale-customized features at each scale, and a Masked Selection and Inheritance Loss (MSIL) that helps to achieve high-quality density maps across all scales. Our experimental results on nine datasets with counting and localization tasks demonstrate the unprecedented scale generalization ability of STEERER. Code is available at https://github.com/taohan10200/STEERER.
LD-ZNet: A Latent Diffusion Approach for Text-Based Image Segmentation

Large-scale pre-training tasks like image classification, captioning, or self-supervised techniques do not incentivize learning the semantic boundaries of objects. However, recent generative foundation models built using text-based latent diffusion techniques may learn semantic boundaries. This is because they have to synthesize intricate details about all objects in an image based on a text description. Therefore, we present a technique for segmenting real and AI-generated images using latent diffusion models (LDMs) trained on internet-scale datasets. First, we show that the latent space of LDMs (z-space) is a better input representation compared to other feature representations like RGB images or CLIP encodings for text-based image segmentation. By training the segmentation models on the latent z-space, which creates a compressed representation across several domains like different forms of art, cartoons, illustrations, and photographs, we are also able to bridge the domain gap between real and AI-generated images. We show that the internal features of LDMs contain rich semantic information and present a technique in the form of LD-ZNet to further boost the performance of text-based segmentation. Overall, we show up to 6% improvement over standard baselines for text-to-image segmentation on natural images. For AI-generated imagery, we show close to 20% improvement compared to state-of-the-art techniques. The project is available at https://koutilya-pnvr.github.io/LD-ZNet/.
An Optoelectronic Analog Ising Machine Enabling 2048-Spin and Low-Latency Calculations

An optoelectronic analog Ising machine is experimentally demonstrated. The SpMV algorithm is applied to accomplish two MAX-CUT tasks mapped into 2048-spin Ising networks, taking only 1.68μs per iteration.
Smart Voting System through Facial Recognition

The International Scientific Research Organization for Science, Engineering and Technology (ISROSET) is a Non-Profit Organization; The ISROSET is dedicated to improvement in academic sectors of Science (Chemistry, Bio-chemistry, Zoology, Botany, Biotechnology, Pharmaceutical Science, Bioscience, Bioinformatics, Biometrics, Biostatistics, Microbiology, Environmental Management, Medical Science, Forensic Science, Home Science, Library Science, Material Science Military Science, Physical Science, Physical Education Science, Educational Science, Fisheries, seed technology, Agriculture, Forestry Science, Mathematics, Physics, Statistics and Geology/Earth Science), Computer Science, Engineering and Information Technology, Commerce, Management, Economics Sociology and Social Science.
Recognition of Facial Expressions and Its Application to Human Computer Interaction

This chapter describes a model that recognizes emotions from not only facial expressions but also human situations. Information on situations is inputted to the model indirectly, which is transformed into 6 basic emotions; happiness, sadness, fear, surprise, anger and disgust. The transformation is performed by the use of questionnaire data. The artificial neural network models to recognize emotions from facial expressions and situations have an input layer, an output layer and some hidden layers. The route decision system searches a route to an instructed destination and expresses a system state with line drawing facial expressions. The recognition model of emotions and the route decision system are combined into a communication model considering facial expressions and situations, where situations are limited into the ones with respect to the route decision. The recognition sections of facial expressions and the situations are necessary in order to combine the route decision system and the recognition model of emotions.
Multi Layer Perceptron Modelling in the Housing Market

The study examines the use of multi layer perception network (MLP) in predicting the price of terrace houses in Kuala Lumpur (KL). Nine factors that significantly influence the price were used in this attempt. Housing data from 1994 to 1996 were presented to the network for training. Tested results from the model obtained for various years were compared using regression analysis. The study provides the predictive ability of the trained MLP model that can be used as an alternative predictor in real estate analysis.
An Interconnected World

Twitter: Dickinson’s first EPA-GRO fellow chats about what she learned on campus and around the world. @EPAresearch. Facebook: Dickinson’s first #EPAgro fellow chats about what she learned on campus and around the world. @EPA GRO fellows 2012-2014
GA-Hard or GA-Easy: A Criticism to Epistasis Analysis

It is necessary to consider what makes problems easy or hard for genetic algorithms. Davidor [Dav91] has examined this question by applying Epistasis Analysis. In this paper, we first give a review of Epistasis Analysis. Then, we apply Epistasis Analysis to certain functions and construct five functions with differing degrees of difficulty for genetic algorithms, some GA-easy and some GA-hard. Finally, experimental results and conclusion are described. Unfortunately, Epistasis Analysis can not accurately estimate the GA-hardness of a function.
Trees and light

Trees and light: How light affects the architecture of the individual tree. Includes an animation on this process.
Does Logic Synthesis Visualization Excite EETs?

Before joining academia, he gained fourteen years of extensive industry experience
Automatically Understanding Handwritten Self-explanations

Research has demonstrated that self-explanation hones student's metacognitive skills and increases their performance.We have found however, that not all self-explanation is substantive.Our goal is to develop computational techniques capable of determining whether a student's explanation is relevant or not.This will then enable us, for example, to create an interactive tutoring system capable of prompting students to continue their explanations when necessary.This is a tractable task as self-explanations typically contain a small number of possible concepts.The language used to express these concepts can vary greatly, but our task is only to identify the existence of the concepts, not to perform general machine interpretation.In this paper, we present early work on the automatic understanding of students' handwritten self-explanation of their solutions to homework problems in an engineering statics course.We employ an open information extraction technique popularly used to identify relations present in broadcast news transcripts.In our study, this technique achieved up to 97% accuracy at identifying when the content of a student's self-explanation did not match the concepts used by experts in explaining their own work on the same problem.
Use Of Tablet Pcs To Generate Class Discussion And Facilitate Deeper Understanding

He also serves as Lead Faculty for the Master of Science in Wireless Communications degree program.He teaches and carries out research in wireless systems, computer security, and applications of advanced technology in education.He also teaches global business.
PENINGKATAN KEAMANAN JARINGAN TERHADAP SERANGAN MALWARE MENGGUNAKAN TEKNIK HONEYPOT DIONAEA

Handling for network security issues require a defense system that uses a firewall, antivirus and intrusion detection systems in the network (network intrusion detection system / NIDS). Security-related attacks through the network with malware could use the honeypot Dionaea. In this research honeypot implementation Dionaea as a shadow server as a diversion attack, while the model of the attack through the network first scan and attack by malware. It is expected that the system is implemented capable of handling network security attacks. Scenario testing in this study were carried out attacks on the system via the internal network and external networks / public use nmap and metasploit. Besides testing in realtime against attack from outside. This model of data retrieval is done for 3 days in a span of 7:00 to 3:00 p.m. On testing over a local network, the public and the public in realtime obtained the system has detected attacks. In the public backlash in realtime leads on port 1433 for MSSQL service, so it requires more handling for systems that use the service.
Integration Of Software Engineering Graduate Education And Continuing Professional Development

McDonald has an extensive industrial background in both software and electrical
Web Enabled Conference Management System

In recent years, with the improvement of internet technologies and hardware supports, we can find that internet have become an important part in our daily life.Thus with the enormous use of the networks, many real world activities are now handled as World Wide Web applications.Our focus in this paper is a complete conference management system, we observe that in the last few years, several web based conference management systems have been developed and are being used by many international conferences all over the world.However, some of these systems are not available for free to the academic community and some of them are restricted in terms of options and flexibility that they provide to the users.Some of the available systems do not support multiple tracks in the conference; some do not provide flexibility to the organizers to be innovative.We present an architecture, as well as a complete system of integrated tools to support planning, organization, management, and execution efforts during the organization and running of a new conference.This paper describes the Web Enabled Conference Management (WECM) System that handles all activities of real-world conferences by relinquishing much of manual control and activities to automatic mechanism.The Conference Management System is the front end to handle the processes of conference organization.It also provides many tools to different members of the conference organizing committee including conference administrator, conference chair, track chairs, program committee and authors, with varying level of access and control.
Program Offerings and Curriculum Convergence Between the Dublin Institute of Technology (DIT) and the University of Maryland, Baltimore County (UMBC)

Recently the Department of Civil and Environmental Engineering (CEE) at UMBC completed the process of revamping its curriculum and preparing a plan to offer a ABET accredited undergraduate degree in Environment and Water Resources Engineering (EWRE).The process began in a difficult economic period which resulted in an increased emphasis on due diligence as whether the program would succeed.The proposed EWRE program would address several UMBC academic priorities and respond to the anticipated increasing demand for training in this discipline.First, the degree program responded to a growing national and statewide initiatives in climate change and the environment.Environmental engineers, in addition to providing safe water and clean air, address many of the emerging issues associated with climate change, clean sources of energy, and sustainable development.The challenges faced by the EWRE profession today are unique and brought about by a rapidly changing world order with respect to the need for sustainable utilization of energy resources, sustainable use of material resources and production practices, proactive environmental management of emerging technologies (e.g.nanomaterials), and sustainable management of shrinking water resources that is increasingly becoming the cause of national and international conflicts.The creation of a new undergraduate engineering degree provides an opportunity to develop a program that embraces new problems and is focused on emerging issues in the field of EWRE.Second, an environmental engineering degree provides an option for UMBC engineering students beyond the available programs (mechanical, chemical/biochemical and computer engineering); this will also likely increase enrollment in UMBC's College of Engineering and Information Technology (COEIT).Third, environmental engineering is the only engineering discipline expected to grow "much faster than the average for all [engineering] occupations" (26% by 2016; http://www.bls.gov/oco/ocos027.htm#outlook).4. A description of any specialized laboratories, equipment or any other significant new resources that will be necessary to offer the program.Currently the Dublin Institute of Technology is facing some of the same issues that catalyzed the UMBC effort.Brian Reed was awarded a Fulbright Scholar Award at DIT and will be part of the effort to address the issues that are facing DIT bringing a perspective that was developed at UMBC.The differences and similarities of the problems and solutions
Research Guides: Basic Math: E-books

This Research Guide provides links to practice problems as well as information about how to find books, e-books, videos and websites that teach basic math concepts.
Software Development For Team Projects In Manufacturing

A software package has been developed to introduce students to the integration of design criteria, material properties, mechanical properties and product cost.The software has been used in the two credit manufacturing processes course for four years and modifications have been made based upon the responses and comments of the students on the assessment questionnaires they completed.The course is required by all mechanical engineering and industrial engineering programs and is scheduled at the junior level.The overview of the typical project, results of the student questionnaires, project changes and software changes are presented.
Broadening Rapid Prototyping Awareness Via P16 Stem Teacher Workshops

The Objectives of the NSF CCLI Phase 1 Award 0536509 are to provide exposure to, and dissemination of, state of the art rapid prototyping technology to educational institutions that do not otherwise have access to such technology.These objectives are accomplished through the development of an Internet based remotely accessible rapid prototyping laboratory.As part of the project deliverables, the project team has been conducting P16 STEM teacher workshops for the last two years.This paper will report on the structure of the workshops, survey data collected from the teachers, and practices that have been implemented by instructors and teachers at their host institutions.
Using Computers To Support Qualitative Understanding Of Causal Reasoning In Engineering

instructional design, computer-based learning, hypermedia, constructivist learning, cognitive tools, and problem solving.His current research focuses on the cognitive processes engaged by problem solving and models and methods for supporting those processes during learning.
Development Of Online Multimedia Based Prototype E Lecture Interface Using Human Like Animated Pedagogical Agent For Effective Dissemination Of Finite Element Method

Multiple e-Learning platforms have been designed, implemented and evaluated over the past decade for effective implementation of teaching and learning in engineering education.This study deals with the development of an interactive prototype interface for the finite element method e-Lecture.The e-Lecture interface integrates life-like animated pedagogical agents, computer mediated communications and multimedia technologies.The use of animated pedagogical agents in engineering education tries to overcome the challenges of current e-Learning techniques with a new effective and efficient intellectual human computer interface.Available animated pedagogical agents with gaze, gesture and voice capabilities are used in the prototype e-Lecture to actively/interactively communicate with the students.New animated pedagogical agents called Mr. and Ms. FEMur (Finite Element Method universal resource) will be used to deliver online finite element method e-Lectures.A prototype e-Lecture interface using Mr. FEMur demonstrates the concepts of "Degree of Freedom" in this paper.These e-Lectures will be integrated into the finite element method learning environment that is a part of bigger effort to develop the FEMur web site.
Experiments With Computer Password Cracking And Shielding Techniques

Internet is dominating almost every aspect of our life.Internet applications are too many in today's business world.It is hard to imagine any office or home without a computer network.All kinds of money transactions are possible today because of the fast changes in computer technology.As a result, everyone with an online account can buy or sell anything over the Internet in a secured environment.Therefore, it is important to secure the computer with the easy username and an unbreakable password.This topic can be integrated into anyone of the Computer Networks or Network Security courses for undergraduate students majoring in Computer Engineering Technology.This paper explains the importance of secured password and examines the kinds of passwords that are breakable.The password cracking uses simple open source software tools available in the Internet.In addition, this paper also discusses different types of password related attacks and password shielding techniques.Summary of the experimental results are also provided for different passwords with various lengths, characters, and complexity.
Implementasi Algoritma Region Growing untuk Segmentasi Retakan Bidang Batuan

Crack is a factor that caused rock discontinuity. Rock discontinuity is an important input variable in slope stability analysis in open pit mining area. Slope stability analysis should be conducted periodically to prevent landslide which can cause damages and fatalities. The data acquisition of rock discontinuity commonly is taking place directly in the field on the slope to be analyzed, which is time consuming and expensive. The objective of this research is to review the image processing application to identify rock discontinuity in particular rock crack. The image processing approach which is applied in this research is segmentation using region growing algorithm. This algorithm was chosen because of its flexibility to reduce noise with tuning the criteria of threshold value. The algorithm was implemented in C++ programming language. 35 image samples were tested to rate the segmentation result. The result shows that this algorithm was quite successful to detect rock cracks. Furthermore the result can be optimized with increase the threshold value to minimize the isolated pixel which is noise.