THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

A systematic literature review of blockchain-based applications: Current status, classification and open issues

Communications of the ACM (CACM for short, not the best sounding acronym around) is the ACM’s flagship magazine. Started in 1957, CACM is handy for keeping up to date on current research being carried out across all topics of computer science and realworld applications. CACM has had an illustrious past with many influential pieces of work and debates started within its pages. These include Hoare’s presentation of the Quicksort algorithm; Rivest, Shamir and Adleman’s description of the first publickey cryptosystem RSA; and Dijkstra’s famous letter against the use of GOTO. In addition to the print edition, which is released monthly, there is a fantastic website (http://cacm.acm. org/) that showcases not only the most recent edition but all previous CACM articles as well, readable online as well as downloadable as a PDF. In addition, the website lets you browse for articles by subject, a handy feature if you want to focus on a particular topic. CACM is really essential reading. Pretty much guaranteed to contain content that is interesting to anyone, it keeps tabs on the latest in computer science. It is a valuable asset for us students, who tend to delve deep into a particular area of CS and forget everything that is happening around us. — Daniel Gooch U ndergraduate research is like a box of chocolates: You never know what kind of project you will get. That being said, there are still a few things you should know to get the most out of the experience.

Communications of the ACM

Hydrogels in sensing applications

Privacy preservation in blockchain based IoT systems: Integration issues, prospects, challenges, and future research directions

This is an extended abstract for a Research Demo Session based on our published work [1]. It is important to be able to reduce the frequency of elderly falls and their disastrous effects. Good-Eye proposes an edge device which predicts or detects falls based on image orientation and physiological sensors using the Internet-of-Medical-Things (IoMT). Using LED lights, the user is notified with the decision of fall prediction and detection if the observed change is greater than a set threshold. Along with a camera attached to the wearable, the Good-Eye system proposes a remote off-line on-wall camera to make more accurate prediction and detection of falls.

Good-Eye: A Device for Automatic Prediction and Detection of Elderly Falls in Smart Homes

In this paper, a new hardware security method is proposed to secure resource-constrained devices using blockchain technology. The new method is utilizing manufacturer parameters of a device, such as PUF, memory, firmware parameters, etc. to create a linked list of unique identification (UID) data, or an identity that could secure, monitor, and act accordingly to ensure device integrity and honesty.

ASID: Accessible Secure Unique Identification File Based Device Security in Next Generation Blockchains

The modeling of the brain as a three-dimensional spatial object, similar to a geographical landscape, has the paved way for the successful application of Kriging methods in solving the seizure detection problem with good performance but in cubic computational time complexity. The Deep Neural Network (DNN) has been widely used for seizure detection due to its effectiveness in classification tasks, although at the cost of a protracted training time. While Kriging exploits the spatial correlation between data locations, DNN relies on its capacity to learn intrinsic representations within the dataset from the basest unit parts. This paper presents a Distributed Kriging-Bootstrapped Deep Neural Network (DNN) model as a twofold solution for fast and accurate seizure detection using brain signals collected with the electroencephalogram (EEG) from healthy subjects and patients of epilepsy. The proposed model parallelizes the Kriging computation into different cores in a machine and then produces a strongly correlated, unified quasi-output data which serves as an input to the Deep Neural Network. Experimental results validate the proposed model as superior to conventional Kriging methods and DNN by training in 91% less time than the basic DNN and about three times as fast as the ordinary Kriging-Bootstrapped Deep Neural Network (DNN) model while maintaining good performance in terms of sensitivity, specificity and testing accuracy compared to other models and existing works.

Elias Kougianos

Papers

Good-Eye: A Device for Automatic Prediction and Detection of Elderly Falls in Smart Homes

ASID: Accessible Secure Unique Identification File Based Device Security in Next Generation Blockchains

Distributed Kriging-Bootstrapped DNN Model for Fast, Accurate Seizure Detection from EEG Signals

Power Reduction Fundamentals

High-Level Synthesis Fundamentals