Tabu search based multiple voltage scheduling under both timing and resource constraints

Lean strategies have been developed to eliminate or reduce waste and thus improve operational efficiency in a manufacturing environment. However, in practice, manufacturers encounter difficulties to select appropriate lean strategies within their resource constraints and to quantitatively evaluate the perceived value of manufacturing waste reduction. This paper presents a methodology developed to quantitatively evaluate the contribution of lean strategies selected to reduce manufacturing wastes within the manufacturers’ resource (time) constraints. A mathematical model has been developed for evaluating the perceived value of lean strategies to manufacturing waste reduction and a step-by-step methodology is provided for selecting appropriate lean strategies to improve the manufacturing performance within their resource constraints. A computer program is developed in MATLAB for finding the optimum solution. With the help of a case study, the proposed methodology and developed model has been validated. A ‘lean strategy-wastes’ correlation matrix has been proposed to establish the relationship between the manufacturing wastes and lean strategies. Using the correlation matrix and applying the proposed methodology and developed mathematical model, authors came out with optimised perceived value of reduction of a manufacturer's wastes by implementing appropriate lean strategies within a manufacturer's resources constraints. Results also demonstrate that the perceived value of reduction of manufacturing wastes can significantly be changed based on policies and product strategy taken by a manufacturer. The proposed methodology can also be used in dynamic situations by changing the input in the programme developed in MATLAB. By identifying appropriate lean strategies for specific manufacturing wastes, a manufacturer can better prioritise implementation efforts and resources to maximise the success of implementing lean strategies in their organisation.

The smart grid systems, in replace of the traditional power grid systems, have been widely used among some well-known telecommunication, IT and power industries. These systems have multiple advantages such as energy efficiency, reliability and self-monitoring. To prevent power outage, threshold based power usage control (PUC) in a smart grid considers a situation where the utility company sets a threshold to control the total power usage of a neighborhood. If the total power usage exceeds the threshold, certain households need to reduce their power consumption. In PUC, the utility company needs to frequently collect power usage data from smart meters. It has been well documented that these power usage data can reveal a person’s daily activity and violate personal privacy. To avoid the privacy concern, privacy-preserving power usage control (P-PUC) protocols have been introduced. However, the existing P-PUC protocols are not very efficient and the computations cannot be outsourced to a cloud server. Thus, the utility company cannot take advantage of the cloud computing paradigm to potentially reduce its operational cost. The goal of this paper is to develop a P-PUC protocol whose computation/execution is outsourceable to a cloud. In addition, the proposed protocol is much more efficient than the existing P-PUC protocols. We will provide extensive empirical study to show the practicality of our proposed protocol.KeywordsSmart gridPrivacy-preservingPower usage control

In this paper, a tabu search-based behavior level synthesis scheme is proposed to minimize power consumption with resource operating at multiple voltages under the timing and the resource constraints. Unlike the conventional methods where only scheduling is considered, our synthesis scheme considers both scheduling and partitioning simultaneously to reduce power consumption due to the functional units as well as the interconnects among them. More importantly, our approach tends to efficiently address a few practical layout problems inherent to multiple voltage designs. In particular, we have configured our solutions as a three-tuple vector to account for both the timing and the partition. Cycling of the same solutions is prevented by applying a tabu list with an update mechanism enhanced with an aspiration function. In this way, the algorithm can search a large solution space with modest computation effort and fast convergence rate. Experiments with a number of DSP benchmarks show that the proposed algorithms achieve an average power reduction by 49.6%.

Nowadays, there appeared a tendency of expanding scope and scale of activities in the Arctic. This is accompanied by the increasing number of security threats and potential emergencies factors in the region. Arctic region development involves implementing the goals of reducing risks to global and regional security. An important role in implementing the strategy of creating a comprehensive security system in the Arctic belongs to efficient protection of population and territories, critically important and potentially dangerous facilities from natural and man-made emergencies. All dangerous factors characterizing emergencies require generation of a complex approach to ensure security in the Arctic territories, increasing the rescue services resource potential and providing monitoring the environment components state and pollution. This article identifies ways to solve the problem of strategic planning and deployment of forces and facilities when creating an integrated security system under resource constraints and dynamically changing situation in the Arctic. An organization chart of strategic resource planning for emergencies management in the Arctic was developed. A decision-making algorithm is proposed to elaborate forces and facilitate composition for the Arctic integrated search-and-rescue centers based on the developed chart. Achieving results in strategic planning involves elaboration of a program for developing forces and facilities of the integrated security system in the Arctic region on the basis of results obtained within the simulation process. The program should reflect step-by-step solution of strategic planning tasks in accordance with goals, resource and time constraints.

Recently, dynamic frequency scaling has been explored at the CPU and system levels for power optimization. Low-power datapath scheduling using multiple supply voltages has been well researched. In this work, we develop new datapath scheduling algorithms that use multiple supply voltages and dynamic frequency clocking in a coordinated manner in order to reduce the energy consumption of datapath circuits. In dynamic frequency clocking, the functional units can be operated at different frequencies depending on the computations occurring within the datapath during a given clock cycle. The strategy is to schedule high-energy units, such as multipliers at lower frequencies, so that they can be operated at lower voltages to reduce energy consumption and the low-energy units, such as adders at higher frequencies, to compensate for speed. The proposed time- and resource-constrained algorithms have been applied to various high-level synthesis benchmark circuits under different time and resource constraints. The experimental results show significant reduction in energy for both the algorithms.

Code generation methods for DSP applications are hampered by the combination of tight timing constraints imposed by the performance requirements of DSP algorithms, and resource constraints imposed by a hardware architecture. In this paper, we present a method for register binding and instruction scheduling based on the exploitation and analysis of resource- and timing constraints. The analysis identifies sequencing constraints between operations additional to the precedence constraints. Without the explicit modeling of these sequencing constraints, a scheduler is often not capable of finding a solution that satisfies the timing, resource and register constraints. The presented approach results in an efficient method of obtaining high quality instruction schedules with low register requirements.

In this paper, a scheduling algorithm for multi-processor real-time systems with relative timing constraints and resource constraints is proposed. The proposed algorithm has the capability to satisfy any timing constraints expressed as inequalities in two variables and a constant. This implies that scheduling problems imposed on various timing constraints such as end-to-end timing constraints and/or relative timing constraints, which are known to be difficult to handle, can be solved. Since the problem addressed in this paper is a generalization of some NP-complete problems, it is difficult to solve efficiently. Thus, the goal of the authors is to derive a heuristic algorithm which performs well on many instances of the problem, although in some cases it will take enormous space and time. Experimental results show that the proposed algorithm achieves a success rate of 80% in 3 minutes of computation time.

Power dissipation is becoming the most challenging design constraint in nanometer technologies. Among various design implementation schemes, standard cell ASICs offer the best power efficiency for high-performance applications. The flexibility of ASICs allow for the use of multiple voltages and multiple thresholds to match the performance of critical regions to their timing constraints, and minimize the power everywhere else. We explore the trade-off between multiple supply voltages and multiple threshold voltages in the optimization of dynamic and static power. The use of multiple supply voltages presents some unique physical and electrical challenges. Level shifters need to be introduced between the various voltage regions. Several level shifter implementations will be shown. The physical layout needs to be designed to ensure the efficient delivery of the correct voltage to various voltage regions. More flexibility can be gained by using appropriate level shifters. We will discuss optimization techniques such as clock skew scheduling which can be effectively used to push performance in a power neutral way.

The low power register scheduling and allocation algorithm is concerned with minimum switching activity and low power multiple voltages. The proposed algorithm executes low power scheduling to reduce switching activity using a shut down technique by the creation of a data flow graph (DFG) from the VHDL description. Also, the low power register allocation algorithm determines the minimum register after the life time analysis of all variables. It minimizes the switching activity using a graph coloring technique for low power consumption. Finally, the total power is reduced by using the low power multiple voltage. The proposed algorithm proves the effect through various filter benchmarks to adopt a low power register scheduling and allocation algorithm considering resource constraint at multiple voltage.

This study explored the use of blended learning in a fashion design class, working within the constructivist orientation with a mixed methods case study and using a sequential exploratory approach in order to focus on the effectiveness of the blended learning design and how it is experienced by the participants. The case study was based on a group of second year fashion design students from a private design institution in South Africa, for the combined subject, pattern making and garment construction. The purpose of this research was to investigate the ways in which face-to-face learning and online learning could best be blended to facilitate instruction in this particular class. The study focused on establishing what combination of online and face-to-face delivery could be seen to be most effective in achieving the project learning outcomes within the time and resource constraints available for the combined pattern making and garment construction subject. A blended learning curriculum model (Huang, Ma and Zhang, 2008) was used to assist in preparation for the blended learning programme, with online learning delivery being effected by means of Google Classroom, the learning management system recommended by the private design institution. The sequential exploratory approach involved two projects, so that insights gained from the first project could be applied to modify the blended learning design for the second project, if and as required. Quantitative data were used to establish a baseline of students’ prior understanding of blended learning, pattern making and garment construction processes. Qualitative data were collected in the form of interviews, questionnaires and observations, allowing for a descriptive understanding of how students as well as the lecturer (who was the researcher) experienced the blended learning classroom, and how effective that blend was in achieving the desired learning outcomes; opportunities were also offered for reflection. The results revealed that, not only did blended learning delivery need to be applied in a developmental way, with ongoing adjustments to accommodate best teaching/learning practice, but also that different fashion ‘briefs’ (that is, the tasks involved) might require modifications to the blended learning delivery design. This suggests that there is no ideal ‘blend’ in blended learning, but that, like other forms of learning, it is exploratory, tentative and constantly evolving. It is hoped that this study will offer insights into how face-to-face and online learning can be combined to best facilitate the learning process in this particular case, where practical assistance with students’ individual design projects traditionally requires a large amount of the instructional time available. As many vocational university subjects have similar time and resource constraints, particularly in facilitating practical application of theory at a professional standard, it is also hoped that, to some extent, the results will be generalizable to other disciplines.

This study aimed to explore what happened in the experiences of eight Grade 3-5 teachers when they provided small group strategies to students with learning disabilities at United Cerebral Palsy of Central Florida, Pine Hills. The research employed semi-structured interviews to investigate difficulties and perceptions. Teachers discussed positive effects on students' performance, engagement, and confidence. But there were many hurdles too, like managing a wide range of behaviors and skill levels, toggling between small-group and whole-group instruction, and meeting the emotional needs of each student. Resource constraints (material, technology, support personnel) only compounded these challenges. Thematic analysis highlighted the following themes: Classroom management, time constraints, different learning requirements, resource constraints, and social-emotional challenges. This study adds to the fund of knowledge by identifying the challenges and successes of small group strategies for LD. The importance of improving teacher preparation about inclusive practice, differentiation, and behaviour management, as well as providing more resources and support staff, is highlighted. Small group instruction significantly improves academic performance among students with learning disabilities by allowing for personalized instruction and increased engagement. However, its success depends on adequate support, including time, staffing, and behavioral strategies, to ensure effective and sustainable implementation. Continuous professional development and strong institutional backing are crucial to empower teachers in delivering dynamic, differentiated instruction tailored to diverse learner needs. Based on the conclusions, it is recommended that schools formally adopt small-group instruction as a core strategy in inclusive education and provide dedicated time and support staff for its implementation. Training in differentiated instruction, behavior management, and collaborative planning should be regularly conducted to equip teachers with inclusive practices. Adequate learning resources, assistive tools, and data-informed grouping strategies are essential to address diverse student needs. Lastly, applying the Enhanced Support Program for Students with Learning Disabilities (ESP-SLD) and fostering teamwork among educators, parents, and peers will strengthen inclusive efforts and improve student outcomes.

A window-assisted video partitioning strategy for partitioning and caching video streams in distributed multimedia systems

The study of whether life exists, is extinct, or not depends on various sophisticated experimental studies, as many different signatures of life can be used. The experimental procedures that can be performed to identify life can be further restricted by time, resources, and mobility constraints. Therefore, any research analyzing the presence of extraterrestrial life must be precise and unambiguous. This research focuses on the objective of the extraterrestrial life detection domain and seeks to provide an efficient protocol that can produce life detection decisions based on empirical data obtained through chemical analysis under time and resource-constrained conditions. While the majority of existing frameworks in this field are designed to identify biomolecules, our goal is to accomplish the same with minimal operational expense and mission complexity. We argue that the thoughtful integration of multiple biomolecular detections with lesser complexity and a robust framework can improve overall mission performance by satisfying the necessary time and resource constraints. In this study, a rapid multiple biomolecules-based life detection protocol (MBLDP-R) from soil samples is developed from scratch and embedded in an operational scientific rover subsystem targeted for planetary analysis missions. The study uses artificial biomolecule samples and simulated extraterrestrial environments to illustrate the suggested protocol’s end-to-end process. First, we list a few significant biomolecules, including lipids, proteins, carbohydrates, nucleic acids, ammonia, and pigments. Then, a weighted qualitative test scoring is applied to sort out the best test method for the finally selected biomolecules which are used as operational analogue to showcase the protocol’s in-situ analysis and decision-making capabilities. Based on the suitable biomolecules, a scientific exploration subsystem is developed, and the implemented protocol is built to perform onboard sample analysis. Evaluation results show that: (1) the proposed MBLDP-R protocol could effectively predict the classes with an average f1-score of 98.65% (macro) and 90.00% (micro), (2) the area under the Receiver Operating Characteristics (AUC-ROC) curve shows the sample categories to be correctly predicted 92% of the time (97% for Extant, 88% for Extinct, and 92% in the case of NPL), and (3) the protocol is time-efficient with an average completion time of 17.60 min, demonstrating the protocol’s rapid nature in detecting biosignatures in soil samples. The research outcome yields useful additional data for related future studies, particularly in the design of scientific frameworks for mission-specific requirements with limited resources while also serving as a reference point for constraint evaluation methods for similar systems.

STARC 2.0: An improved pert network simulation tool

This study examined teachers' abilities to implement Prezi-assisted PowerPoint media in elementary classroom instruction within a rural school context. Despite technological availability, effective integration of interactive multimedia remains challenging, particularly in resource-limited settings where infrastructural and capacity constraints impede implementation. A qualitative descriptive case study was conducted at SD Inpres 1 Kaluku Tinggu, Central Sulawesi, Indonesia, involving a Grade V teacher selected through purposive sampling. Data were collected through classroom observations, semi-structured interviews, and documentation analysis, then analyzed using Miles and Huberman's framework involving data reduction, display, and verification. Findings revealed that the teacher demonstrated strong competence in instructional planning, classroom implementation, and formative assessment. Prezi-assisted PowerPoint significantly enhanced student engagement, with documented increases in student-initiated questions (47 versus 12 in conventional lessons) and participation rates. The teacher exhibited self-directed professional development, pedagogical reasoning, and adaptive strategies to overcome infrastructural challenges including limited internet connectivity and time constraints. The study confirms that effective technology integration depends primarily on teacher readiness and pedagogical skills rather than solely on infrastructural availability. Theoretically, findings extend multimedia learning and constructivist theories to authentic elementary contexts with resource constraints. Practically, results underscore the necessity for continuous professional development emphasizing pedagogical technology integration and institutional support systems addressing both technical and attitudinal barriers to sustainable innovation.