The process of organizational communication: a model and fieldstudy

Research in computer-mediated communication has usually emphasized the cognitive over the social aspects of communication, the medium over the message, and the product of communication over the process. In contrast, this paper emphasizes three constructs of the communication process: goal-based communication strategies, message form and medium. We seek to balance cognitive and social communication strategies and to combine new and old measures of the message form (organization, formality and size). A field study in an academic institution examined the content of text-based communication delivered by letter, memo, fax and e-mail. As expected, people preferred certain message and medium attributes for certain strategies. These findings are further investigated using open-ended interviews. We conclude with examples of practical implications on designing and implementing computer-mediated communication     

VLSI mask optimization: From shallow to deep learning

VLSI mask optimization is one of the most critical stages in manufacturability aware design, which is costly due to the complicated mask optimization and lithography simulation. Recent researches have shown prominent advantages of machine learning techniques dealing with complicated and big data problems, which bring potential of dedicated machine learning solution for DFM problems and facilitate the VLSI design cycle. However, uncertainty nature of state-of-the-art machine learning models have posed great challenges when developing alternative solutions. In this paper, we focus on a heterogeneous OPC framework that assists mask layout optimization. Instead of fitting neural networks for mask optimization tasks directly, a multi-class classification model is developed to capture design characteristics and hence determine the most suitable OPC engines. Experimental results have shown the efficiency and effectiveness of proposed frameworks that have the potential to be alternatives to existing EDA solutions.     

The copy-exactly ramp-up strategy: trading-off learning with process change

Production ramp-up is the period of time during which a manufacturing process is scaled up from a small laboratory-like environment to high-volume production. During this scale-up, the firm needs to overcome the numerous discrepancies between how the process is specified to operate as written in the process recipe and how it actually is operated at large volume. The reduction of these discrepancies, a process that we will refer to as learning, will lead to improved production yields and higher output. In addition to its learning effort, however, the firm also attempts to change the process recipe itself, which can be in direct conflict with the learning objective. We formalize this intertemporal tradeoff between learning and process change in the form of a dynamic optimization problem. Our model explains the idea of a "copy-exactly" ramp-up, which freezes the process for some time period, i.e., does not allow for any change in the process. Mathematically, this corresponds to a process improvement policy which delays process changes, thereby exhibiting a nonmonotone trajectory, which we show to be optimal if the initial knowledge level is low, the lifecycle short and demand growth is steep, and learning is difficult.     

A novel approach to multiagent reinforcement learning: utilizing OLAP mining in the learning process

Reinforcement learning is considered as a strong method for learning in multiagent systems environments. However, it still has some drawbacks, including modeling other learning agents present in the domain as part of the state of the environment, and some states are much less experienced than others, or some state-action pairs are never visited during the learning phase. Further, before the learning process is completed, an agent cannot exhibit a certain behavior in some states that may be sufficiently experienced. This shows that learning in a partially observable and dynamic multiagent systems environment still constitutes a difficult and major research problem that is worth further investigation. Motivated by this, in this paper, a novel learning approach that integrates online analytical processing (OLAP)-based data mining into the process is proposed. First, a data cube OLAP architecture that facilitates effective storage and processing of the state information reported by agents is described. This way, the action of the other agent, even one not in the visual environment of the agent under consideration, can simply be estimated by extracting online association rules, a well-known data mining technique, from the constructed data cube. Then, a new action selection model that is also based on association rules mining is presented. Finally, states that are not sufficiently experienced by mining multiple-level association rules from the proposed data cube are generalized. Experiments conducted on a well-known pursuit domain show the robustness and effectiveness of the proposed learning approach.     

A quad-rotor system for driving and flying missions by tilting mechanism of rotors: From design to control

This article presents the hybrid design and control of a quad-rotor system called Flymobile. Flymobile is a combined system of a mobile robot and a quad-rotor system aimed to perform both flying and driving tasks. Flymobile performs flying tasks in the same way as conventional quad-rotor systems while the tilting mechanism of each rotor allows Flymobile to navigate in its terrain for a driving task. The body frame with rotors is implemented by a calibration process through a test-bed equipped with a force sensor. The triangular wheel frame is designed to mimic motions of a mobile robot with three passive wheels. Sensor data of a gyro and an accelerometer are filtered and used for controlling the attitude of the system. Focusing on a practical approach of implementing a hybrid system, a non model-based approach is applied to control Flymobile. Experimental studies are demonstrated to show the feasibility of performing both driving and flying missions.     

Advanced learning tools: From real needs to useful student support [Instrumentation Notes]

Advanced learning tools that use current technologies such as informatics, electronics, and sensors can improve the efficiency of student laboratory sessions. Based on remote teaching [1], [2] and advanced monitoring tools [3], [4], [5], these laboratories can improve student learning so much that they effectively change the laboratory teaching approach. This "assisted educational activity" can be extended to cover a large set of student and school needs. The main advantages of these systems are: · a large number of students can use the same equipment; · fewer tutors are needed; · scheduling student labs is much easier; · a more effective teaching activity is possible; · they allow distance learning; and · they can be adapted for students with different needs, including the visually impaired. Educational tools discussed in this column that have been developed by researchers at the DIEES department of the University of Catania [6] are a Computer Science Class Teaching Aid for the Visually Impaired, several Virtual Instruments, and online laboratory sessions for electrical and electronic measurement courses. An interactive environment has also been developed to reduce the time needed to write an accurate technical report [3]. A common word processor (PC) used for writing technical papers is connected via the network (either local or Internet) to a host computer that has an interactive set of digital instruments. The PC uses suitable routines implemented in SCPI language (Standard Command for Programmable Instruments) to allow local control of the digital instruments.     

Preventing insider threats to enhance organizational security: The role of opportunity-reducing techniques

Insider threats are one of the major potential risks jeopardizing organizational security. Many organizations have applied opportunity-reducing techniques to enhance security. These techniques have been classified into hard and soft forms based on their potential propensity to infringe on employees’ personal space. Hard form techniques have been widely adopted owing to their efficiency in saving cost and time. However, this study argues that hard form techniques would restrict personal autonomy, leading employees to disrespect the organizational security policies. To test the research hypotheses, a scenario-based questionnaire survey was conducted on 5,158 Prolific Academic members with working experience in the service industry and research and development, and the information industry. Two hundred and fifty-nine valid responses were analyzed using partial least square based structural equation modeling (PLS-SEM). The results show that the hard form techniques induce employees to feel intrusion of their privacy, making them morally irresponsible for their behavior, and even committing an insider attack. Hard form techniques can produce an adverse effect that is opposite to the intended purpose. The results imply that the practical method of making hard controls less intrusive, including the implementation of soft controls and horizontal decision-making processes for security policies, should be explored.     

Undergraduate electromagnetics laboratory: An invaluable part ofthe learning process

A newly developed pair of undergraduate courses in applied electromagnetics (EM) has succeeded in transforming student attitudes towards EM from dread and avoidance to acceptance and appreciation. One concrete measure of this change is in the enrolment figures in follow-up courses in microwave circuits and microwave propagation-within one year, the enrolments have doubled in one of them and just about tripled in the other one. The new EM courses incorporate an integrative approach towards teaching EM phenomena; this includes a new text, a large number of class demonstrations, and a laboratory component consisting of nine laboratory exercises and a final team project. This paper focuses on design and content of the instructional laboratory and learning contribution it provides     

Compressive sensing and sparse decomposition in precision machining process monitoring: From theory to applications

Precision machining has been claimed to be the backbone to modern industry. It has been widely applied to the key parts’ production in the aerospace, medical and automotive industries. One of the main problems related to precision machining productivity and safety is the machining condition. By utilizing the acquired information from sensory measurements to direct the further actions, the signal processing bridges the gap between human instruction and full automation. Traditional signal acquisition and processing methods are mainly based on Shannon’s Sampling theory, Fourier methods or wavelet analysis. While these techniques meet challenges in precision machining environment, such as machining at high speed, low signal to noise ratio, and high sampling rate. These factors limit their applications especially the online monitoring implementation. The newly developed compressive sensing theory and sparse decomposition techniques provide a possible solution to these problems, while limited studies have been investigated. This paper serves as an introduction to the theory and shows the theory’s potentials in machining condition monitoring by reviewing related literatures and demonstrating case studies from real experiments.     

Fatigue driving detection based on Haar feature and extreme learning machine

As the significant branch of intelligent vehicle networking technology, the intelligent fatigue driving detection technology has been introduced into the paper in order to recognize the fatigue state of the vehicle driver and avoid the traffic accident. The disadvantages of the traditional fatigue driving detection method have been pointed out when we study on the traditional eye tracking technology and traditional artificial neural networks. On the basis of the image topological analysis technology, Haar like features and extreme learning machine algorithm, a new detection method of the intelligent fatigue driving has been proposed in the paper. Besides, the detailed algorithm and realization scheme of the intelligent fatigue driving detection have been put forward as well. Finally, by comparing the results of the simulation experiments, the new method has been verified to have a better robustness, efficiency and accuracy in monitoring and tracking the drivers’ fatigue driving by using the human eye tracking technology.     

From business reengineering to business process change management:a longitudinal study of trends and practices

Business process reengineering has been prominently discussed and implemented in a large number of firms around the world. While the notion of radical change is intuitively appealing to “fix” organizational woes, it has not always met with the degree of success originally claimed by its many proponents. This article studies the evolution of the reengineering concept and its evolution toward the broader notion of process change management. Reported here are the results of two studies that explore reengineering from a project implementation perspective and an organizational perspective at two different points in time. The results show remarkable consistency in the importance of nontechnology management issues concerning strategy, change and people. Further, the notion of continuous change seems to be becoming,more important. The study provides a foundation for identifying key variables that can be studied in order to effectively manage this multifaceted phenomenon     

The case for organizational communication

Three books that provide an overview of current practice in organization communication, look into the future of the field, and a penetrating critique of key assumptions and definitions are reviewed. Several of the issues under consideration-especially organizational culture, generalisation conflicts, and the relationship between communication and productivity-are of special interest to the business community. It is concluded that the issues raised demand consideration by everyone in an organization who writes and speaks on the job, from engineers and managers to technical writers     

Autonomous driving in the uncertain traffic—— a deep reinforcement learning approach

Driving in the complex traffic safely and efficiently is a difficult task for autonomous vehicle because of the stochastic characteristics of engaged human drivers. Deep reinforcement learning (DRL), which combines the abstract representation capability of deep learning (DL) and the optimal decision making and control capability of reinforcement learning (RL), is a good approach to address this problem. Traffic environment is built up by combining intelligent driver model (IDM) and lane-change model as behavioral model for vehicles. To increase the stochastic of the established traffic environment, tricks such as defining a speed distribution with cutoff for traffic cars and using various politeness factors to represent distinguished lane-change style, are taken. For training an artificial agent to achieve successful strategies that lead to the greatest long-term rewards and sophisticated maneuver, deep deterministic policy gradient (DDPG) algorithm is deployed for learning. Reward function is designed to get a trade-off between the vehicle speed, stability and driving safety. Results show that the proposed approach can achieve good autonomous maneuvering in a scenario of complex traffic behavior through interaction with the environment.     

From Atoms to Lives: The Evolution of Nanoparticle Assemblies

Nanoparticle (NP) assemblies have been studied over the past several decades, and the field is advancing more quickly and reaching into more diverse fields. Reports issued from academic and industrial laboratories have driven these advances. Countless breakthroughs have been reported in widely different fields, including thermoelectronics, photoelectronics, catalysts, energy sources, and medical carriers. A “family tree” is clearly needed to accurately trace the developments in the study of NP assemblies. This review uses the unconventional approach of comparing the atomic and NP worlds to describe the development of NP research during the past several decades. The corresponding classifications, such as atoms and NPs, molecules and molecular‐type NP assemblies, crystals and crystalline‐type NP assemblies, biological organisms and analogous artificial assemblies, and biologically functional NP complex assemblies, are discussed in detail. It concludes with remarks concerning the trend from nonliving to living applications of NP assemblies.     

Competing values in software process improvement: an assumption analysis of CMM from an organizational culture perspective

The capability maturity model (CMM) approach to software process improvement is the most dominant paradigm of organizational change that software organizations implement. While some organizations have achieved various levels of success with the CMM, the vast majority have failed. In this paper, we investigate the assumptions about organizational culture embedded in the CMM models and we discuss their implications for software process improvement (SPI) initiatives. In this paper, we utilize the well-known competing values model to surface and analyze the assumptions underlying the CMM. Our analysis reveals contradictory sets of assumptions about organizational culture in the CMM approach. We believe that an understanding of these contradictions can help researchers address some of the difficulties that have been observed in implementing and institutionalizing SPI programs in organizations. Further, this research can help to open up a much-needed line of research that would examine the organization theory assumptions that underpin CMM. This type of research is important if CMM is to evolve as an effective organizational change paradigm for software organizations.     

The five pillars of organizational excellence

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The organizational impact of docket 19880

The field of emergency medical services (EMS)provides an organizational and operational environment which lacks the geopolitical structure and discipline of other public safety services. The opportunity to rearrange the various service provider elements of EMS into a unified regional agency is not likely in current political and economic circumstances. The new EMS radio communications structure which has evolved from Federal Communications Commission Docket 19880 provides the opportunity for operational order and discipline within the various provider elements of EMS. Despite the opportunity for creating the common system approach to EMS communications, many human elements must be dealt with in breaking down traditional barriers to change.     

The Pioneer 10/11 Program: From 1969 to 1994

The Pioneer 10/11 program began in the summer of 1969 and had as its objective the exploration of the Asteroid Belt?that region between Mars and Jupiter?and the exploration of Jupiter. Two flight spacecraft were built?Pioneer 10 and Pioneer 11. Pioneer 10 was launched in 1972 March, passed by Jupiter in 1973 December, and continued on a trajectory that will allow it to escape the solar system. Thus Pioneer 10 became the first man-made object to pass successfully through the Asteroid Belt, to encounter Jupiter, and to escape from the solar system. Pioneer 11 was launched in 1973 April and passed by Jupiter in 1974 December. As a result of Jupiter's influence on its trajectory, it turned around at Jupiter, crossed back through the solar system, then beyond the orbits of Mars and Jupiter, and then encountered Saturn in 1979 September. This encounter was beyond the original objectives and was made possible by the long life and reliability of the spacecraft. Pioneer 11 became the first man-made object to encounter Saturn. At present, Pioneer 11 is also on a solar-escape trajectory although in the opposite direction from Pioneer 10.     

From phones to football: The changing strategic focus of BT

For over a decade BT has been investing significant sums to shift its focus away from the provision of voice telephony towards the Internet. This shift is epitomised by the widespread availability of broadband and the company’s purchase of the rights to broadcast English Premier League football games. This paper argues that its dominance in the voice telephony market funded its initial expansion into these new markets, and that broadband and sports content are mutually supportive lines of business. The paper also highlights the significant contribution that Openreach makes to the overall profitability of BT, and the challenges that exist as a result.